{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Time Series of Phytoplankton Bloom Timing and Environmental Drivers from 2015-2019 at Station S3 (201905 model run)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib as mpl\n",
    "import netCDF4 as nc\n",
    "import datetime as dt\n",
    "from salishsea_tools import evaltools as et, places, viz_tools, visualisations\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import pickle\n",
    "import os\n",
    "import bloomdrivers\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "iyear=2010\n",
    "startjan=dt.datetime(iyear,1,1)  # january start date\n",
    "endmar=dt.datetime(iyear,4,1)   # march end date (doesnt include this value)\n",
    "dateslist=[[dt.datetime(iyear,1,1),dt.datetime(iyear,1,31)],\n",
    "           [dt.datetime(iyear,1,31),dt.datetime(iyear,2,28)], # don't forget leap years: 2020,2016,2012,2008\n",
    "           [dt.datetime(iyear,2,28),dt.datetime(iyear,4,1)]]\n",
    "year=str(iyear)\n",
    "forbloomstart=dt.datetime(iyear,2,15) # long time frame to capture spring bloom date\n",
    "forbloomend=dt.datetime(iyear,6,15)\n",
    "modver='201905'\n",
    "loc='S3'\n",
    "\n",
    "savedir='/ocean/aisabell/MEOPAR/extracted_files'\n",
    "\n",
    "fname=f'JanToMarch_TimeSeries_{year}_{loc}_{modver}.pkl'\n",
    "fname2=f'JanToMarch_TimeSeries_{year}_{modver}.pkl' # for non-location specific variables\n",
    "fname3=f'springBloomTime_{year}_{loc}_{modver}.pkl'\n",
    "savepath=os.path.join(savedir,fname)\n",
    "savepath2=os.path.join(savedir,fname2)\n",
    "savepath3=os.path.join(savedir,fname3)\n",
    "recalc=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.1363636363636362"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "loc='S3'\n",
    "\n",
    "# lat and lon informatin for place:\n",
    "lon,lat=places.PLACES['S3']['lon lat']\n",
    "# get place information on SalishSeaCast grid:\n",
    "ij,ii=places.PLACES['S3']['NEMO grid ji']\n",
    "# GEM2.5 grid ji is atm forcing grid for ops files\n",
    "jw,iw=places.PLACES['S3']['GEM2.5 grid ji']\n",
    "\n",
    "fig, ax = plt.subplots(1,1,figsize = (6,6))\n",
    "with xr.open_dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/mesh_mask201702.nc') as mesh:\n",
    "    ax.contour(mesh.nav_lon,mesh.nav_lat,mesh.tmask.isel(t=0,z=0),[0.1,],colors='k')\n",
    "    tmask=np.array(mesh.tmask)\n",
    "    gdept_1d=np.array(mesh.gdept_1d)\n",
    "    e3t_0=np.array(mesh.e3t_0)\n",
    "ax.plot(lon, lat, '.', markersize=14, color='red')\n",
    "ax.set_ylim(48,50)\n",
    "ax.set_xlim(-125,-122)\n",
    "ax.set_title('Location of Station S3')\n",
    "ax.set_xlabel('Longitude')\n",
    "ax.set_ylabel('Latitude')\n",
    "viz_tools.set_aspect(ax,coords='map')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### location specific variables for environmental driver analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Resulting object does not have monotonic global indexes along dimension time_counter",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-35-d07bc4e1b14a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mjW\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0miW\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwopsdir\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwnam_fmt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbloomdrivers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetWindVarsYear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miyear\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mflist2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0met\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_model_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwopsdir\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwnam_fmt\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mflen\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mftype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'None'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtres\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m24\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mwinds\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_mfdataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mflist2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'paths'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/envs/py39/lib/python3.9/site-packages/xarray/backends/api.py\u001b[0m in \u001b[0;36mopen_mfdataset\u001b[0;34m(paths, chunks, concat_dim, compat, preprocess, engine, lock, data_vars, coords, combine, autoclose, parallel, join, attrs_file, **kwargs)\u001b[0m\n\u001b[1;32m    974\u001b[0m             \u001b[0;31m# Redo ordering from coordinates, ignoring how they were ordered\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    975\u001b[0m             \u001b[0;31m# previously\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 976\u001b[0;31m             combined = combine_by_coords(\n\u001b[0m\u001b[1;32m    977\u001b[0m                 \u001b[0mdatasets\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    978\u001b[0m                 \u001b[0mcompat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompat\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/py39/lib/python3.9/site-packages/xarray/core/combine.py\u001b[0m in \u001b[0;36mcombine_by_coords\u001b[0;34m(datasets, compat, data_vars, coords, fill_value, join, combine_attrs)\u001b[0m\n\u001b[1;32m    787\u001b[0m             \u001b[0mindexes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconcatenated\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindexes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    788\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mindexes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_monotonic_increasing\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindexes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_monotonic_decreasing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 789\u001b[0;31m                 raise ValueError(\n\u001b[0m\u001b[1;32m    790\u001b[0m                     \u001b[0;34m\"Resulting object does not have monotonic\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    791\u001b[0m                     \u001b[0;34m\" global indexes along dimension {}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Resulting object does not have monotonic global indexes along dimension time_counter"
     ]
    }
   ],
   "source": [
    "start=dt.datetime(iyear,2,6)\n",
    "end=dt.datetime(iyear,2,8)#6-8\n",
    "jW,iW,wopsdir,wnam_fmt=bloomdrivers.getWindVarsYear(iyear)\n",
    "flist2=et.index_model_files(start,end,wopsdir,wnam_fmt,flen=1,ftype='None',tres=24)\n",
    "winds=xr.open_mfdataset(flist2['paths'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
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       "                                               paths        t_0        t_n\n",
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       "1  /results/forcing/atmospheric/GEM2.5/gemlam/gem... 2010-02-07 2010-02-08"
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   "execution_count": 41,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time_counter&#x27; (time_counter: 24)&gt;\n",
       "array([&#x27;2010-02-05T00:00:00.000000000&#x27;, &#x27;2010-02-05T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T02:00:00.000000000&#x27;, &#x27;2010-02-05T03:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T04:00:00.000000000&#x27;, &#x27;2010-02-05T05:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T06:00:00.000000000&#x27;, &#x27;2010-02-05T07:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T08:00:00.000000000&#x27;, &#x27;2010-02-05T09:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T10:00:00.000000000&#x27;, &#x27;2010-02-05T11:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T12:00:00.000000000&#x27;, &#x27;2010-02-06T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T14:00:00.000000000&#x27;, &#x27;2010-02-06T15:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T16:00:00.000000000&#x27;, &#x27;2010-02-06T17:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T18:00:00.000000000&#x27;, &#x27;2010-02-06T19:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T20:00:00.000000000&#x27;, &#x27;2010-02-06T21:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T22:00:00.000000000&#x27;, &#x27;2010-02-06T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * time_counter  (time_counter) datetime64[ns] 2010-02-05 ... 2010-02-06T23:...\n",
       "Attributes:\n",
       "    axis:           T\n",
       "    cell_methods:   time_counter: mean\n",
       "    long_name:      Time axis\n",
       "    standard_name:  time\n",
       "    time_origin:    1950-01-01 00:00:00\n",
       "    title:          Time</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time_counter'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time_counter</span>: 24</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a9f8ec6f-d838-4aab-ab3c-2f03607210dd' class='xr-array-in' type='checkbox' checked><label for='section-a9f8ec6f-d838-4aab-ab3c-2f03607210dd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2010-02-05 2010-02-05T01:00:00 ... 2010-02-06T23:00:00</span></div><div class='xr-array-data'><pre>array([&#x27;2010-02-05T00:00:00.000000000&#x27;, &#x27;2010-02-05T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T02:00:00.000000000&#x27;, &#x27;2010-02-05T03:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T04:00:00.000000000&#x27;, &#x27;2010-02-05T05:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T06:00:00.000000000&#x27;, &#x27;2010-02-05T07:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T08:00:00.000000000&#x27;, &#x27;2010-02-05T09:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T10:00:00.000000000&#x27;, &#x27;2010-02-05T11:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T12:00:00.000000000&#x27;, &#x27;2010-02-06T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T14:00:00.000000000&#x27;, &#x27;2010-02-06T15:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T16:00:00.000000000&#x27;, &#x27;2010-02-06T17:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T18:00:00.000000000&#x27;, &#x27;2010-02-06T19:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T20:00:00.000000000&#x27;, &#x27;2010-02-06T21:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T22:00:00.000000000&#x27;, &#x27;2010-02-06T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-849a012d-6ff9-492f-9226-b0af9a30bd02' class='xr-section-summary-in' type='checkbox'  checked><label for='section-849a012d-6ff9-492f-9226-b0af9a30bd02' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_counter</span></div><div class='xr-var-dims'>(time_counter)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-02-05 ... 2010-02-06T23:00:00</div><input id='attrs-656ebf8a-b2dc-4059-8347-e4f380f259ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-656ebf8a-b2dc-4059-8347-e4f380f259ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ceef7e3-4d84-4b11-8b8d-57f75e7ee8d4' class='xr-var-data-in' type='checkbox'><label for='data-1ceef7e3-4d84-4b11-8b8d-57f75e7ee8d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>cell_methods :</span></dt><dd>time_counter: mean</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>1950-01-01 00:00:00</dd><dt><span>title :</span></dt><dd>Time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-02-05T00:00:00.000000000&#x27;, &#x27;2010-02-05T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T02:00:00.000000000&#x27;, &#x27;2010-02-05T03:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T04:00:00.000000000&#x27;, &#x27;2010-02-05T05:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T06:00:00.000000000&#x27;, &#x27;2010-02-05T07:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T08:00:00.000000000&#x27;, &#x27;2010-02-05T09:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T10:00:00.000000000&#x27;, &#x27;2010-02-05T11:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-05T12:00:00.000000000&#x27;, &#x27;2010-02-06T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T14:00:00.000000000&#x27;, &#x27;2010-02-06T15:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T16:00:00.000000000&#x27;, &#x27;2010-02-06T17:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T18:00:00.000000000&#x27;, &#x27;2010-02-06T19:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T20:00:00.000000000&#x27;, &#x27;2010-02-06T21:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T22:00:00.000000000&#x27;, &#x27;2010-02-06T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-61e5252f-b366-48d2-a940-c2c154e1188b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-61e5252f-b366-48d2-a940-c2c154e1188b' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>cell_methods :</span></dt><dd>time_counter: mean</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>1950-01-01 00:00:00</dd><dt><span>title :</span></dt><dd>Time</dd></dl></div></li></ul></div></div>"
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       "<xarray.DataArray 'time_counter' (time_counter: 24)>\n",
       "array(['2010-02-05T00:00:00.000000000', '2010-02-05T01:00:00.000000000',\n",
       "       '2010-02-05T02:00:00.000000000', '2010-02-05T03:00:00.000000000',\n",
       "       '2010-02-05T04:00:00.000000000', '2010-02-05T05:00:00.000000000',\n",
       "       '2010-02-05T06:00:00.000000000', '2010-02-05T07:00:00.000000000',\n",
       "       '2010-02-05T08:00:00.000000000', '2010-02-05T09:00:00.000000000',\n",
       "       '2010-02-05T10:00:00.000000000', '2010-02-05T11:00:00.000000000',\n",
       "       '2010-02-05T12:00:00.000000000', '2010-02-06T01:00:00.000000000',\n",
       "       '2010-02-06T14:00:00.000000000', '2010-02-06T15:00:00.000000000',\n",
       "       '2010-02-06T16:00:00.000000000', '2010-02-06T17:00:00.000000000',\n",
       "       '2010-02-06T18:00:00.000000000', '2010-02-06T19:00:00.000000000',\n",
       "       '2010-02-06T20:00:00.000000000', '2010-02-06T21:00:00.000000000',\n",
       "       '2010-02-06T22:00:00.000000000', '2010-02-06T23:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * time_counter  (time_counter) datetime64[ns] 2010-02-05 ... 2010-02-06T23:...\n",
       "Attributes:\n",
       "    axis:           T\n",
       "    cell_methods:   time_counter: mean\n",
       "    long_name:      Time axis\n",
       "    standard_name:  time\n",
       "    time_origin:    1950-01-01 00:00:00\n",
       "    title:          Time"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f1=xr.open_dataset(flist2.paths[0])\n",
    "f1.time_counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
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       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time_counter&#x27; (time_counter: 24)&gt;\n",
       "array([&#x27;2010-02-06T00:00:00.000000000&#x27;, &#x27;2010-02-06T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T02:00:00.000000000&#x27;, &#x27;2010-02-06T03:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T04:00:00.000000000&#x27;, &#x27;2010-02-06T05:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T06:00:00.000000000&#x27;, &#x27;2010-02-06T07:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T08:00:00.000000000&#x27;, &#x27;2010-02-06T09:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T10:00:00.000000000&#x27;, &#x27;2010-02-06T11:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T12:00:00.000000000&#x27;, &#x27;2010-02-07T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T14:00:00.000000000&#x27;, &#x27;2010-02-07T15:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T16:00:00.000000000&#x27;, &#x27;2010-02-07T17:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T18:00:00.000000000&#x27;, &#x27;2010-02-07T19:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T20:00:00.000000000&#x27;, &#x27;2010-02-07T21:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T22:00:00.000000000&#x27;, &#x27;2010-02-07T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * time_counter  (time_counter) datetime64[ns] 2010-02-06 ... 2010-02-07T23:...\n",
       "Attributes:\n",
       "    axis:           T\n",
       "    cell_methods:   time_counter: mean\n",
       "    long_name:      Time axis\n",
       "    standard_name:  time\n",
       "    time_origin:    1950-01-01 00:00:00\n",
       "    title:          Time</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time_counter'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time_counter</span>: 24</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b588e49e-1a96-4931-960f-177beeb617cd' class='xr-array-in' type='checkbox' checked><label for='section-b588e49e-1a96-4931-960f-177beeb617cd' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2010-02-06 2010-02-06T01:00:00 ... 2010-02-07T23:00:00</span></div><div class='xr-array-data'><pre>array([&#x27;2010-02-06T00:00:00.000000000&#x27;, &#x27;2010-02-06T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T02:00:00.000000000&#x27;, &#x27;2010-02-06T03:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T04:00:00.000000000&#x27;, &#x27;2010-02-06T05:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T06:00:00.000000000&#x27;, &#x27;2010-02-06T07:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T08:00:00.000000000&#x27;, &#x27;2010-02-06T09:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T10:00:00.000000000&#x27;, &#x27;2010-02-06T11:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T12:00:00.000000000&#x27;, &#x27;2010-02-07T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T14:00:00.000000000&#x27;, &#x27;2010-02-07T15:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T16:00:00.000000000&#x27;, &#x27;2010-02-07T17:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T18:00:00.000000000&#x27;, &#x27;2010-02-07T19:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T20:00:00.000000000&#x27;, &#x27;2010-02-07T21:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T22:00:00.000000000&#x27;, &#x27;2010-02-07T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-eb721114-aaea-42d9-832c-4bb59979a71d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb721114-aaea-42d9-832c-4bb59979a71d' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_counter</span></div><div class='xr-var-dims'>(time_counter)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-02-06 ... 2010-02-07T23:00:00</div><input id='attrs-3c95b037-069c-4891-960a-4c27132c5d38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c95b037-069c-4891-960a-4c27132c5d38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9f0bdb2-3e81-4eae-8c4e-5c1ed779d8c1' class='xr-var-data-in' type='checkbox'><label for='data-e9f0bdb2-3e81-4eae-8c4e-5c1ed779d8c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>cell_methods :</span></dt><dd>time_counter: mean</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>1950-01-01 00:00:00</dd><dt><span>title :</span></dt><dd>Time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-02-06T00:00:00.000000000&#x27;, &#x27;2010-02-06T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T02:00:00.000000000&#x27;, &#x27;2010-02-06T03:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T04:00:00.000000000&#x27;, &#x27;2010-02-06T05:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T06:00:00.000000000&#x27;, &#x27;2010-02-06T07:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T08:00:00.000000000&#x27;, &#x27;2010-02-06T09:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T10:00:00.000000000&#x27;, &#x27;2010-02-06T11:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-06T12:00:00.000000000&#x27;, &#x27;2010-02-07T01:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T14:00:00.000000000&#x27;, &#x27;2010-02-07T15:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T16:00:00.000000000&#x27;, &#x27;2010-02-07T17:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T18:00:00.000000000&#x27;, &#x27;2010-02-07T19:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T20:00:00.000000000&#x27;, &#x27;2010-02-07T21:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-07T22:00:00.000000000&#x27;, &#x27;2010-02-07T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4958d437-1241-40e0-a89e-5f23befc405f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4958d437-1241-40e0-a89e-5f23befc405f' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>cell_methods :</span></dt><dd>time_counter: mean</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>1950-01-01 00:00:00</dd><dt><span>title :</span></dt><dd>Time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'time_counter' (time_counter: 24)>\n",
       "array(['2010-02-06T00:00:00.000000000', '2010-02-06T01:00:00.000000000',\n",
       "       '2010-02-06T02:00:00.000000000', '2010-02-06T03:00:00.000000000',\n",
       "       '2010-02-06T04:00:00.000000000', '2010-02-06T05:00:00.000000000',\n",
       "       '2010-02-06T06:00:00.000000000', '2010-02-06T07:00:00.000000000',\n",
       "       '2010-02-06T08:00:00.000000000', '2010-02-06T09:00:00.000000000',\n",
       "       '2010-02-06T10:00:00.000000000', '2010-02-06T11:00:00.000000000',\n",
       "       '2010-02-06T12:00:00.000000000', '2010-02-07T01:00:00.000000000',\n",
       "       '2010-02-07T14:00:00.000000000', '2010-02-07T15:00:00.000000000',\n",
       "       '2010-02-07T16:00:00.000000000', '2010-02-07T17:00:00.000000000',\n",
       "       '2010-02-07T18:00:00.000000000', '2010-02-07T19:00:00.000000000',\n",
       "       '2010-02-07T20:00:00.000000000', '2010-02-07T21:00:00.000000000',\n",
       "       '2010-02-07T22:00:00.000000000', '2010-02-07T23:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * time_counter  (time_counter) datetime64[ns] 2010-02-06 ... 2010-02-07T23:...\n",
       "Attributes:\n",
       "    axis:           T\n",
       "    cell_methods:   time_counter: mean\n",
       "    long_name:      Time axis\n",
       "    standard_name:  time\n",
       "    time_origin:    1950-01-01 00:00:00\n",
       "    title:          Time"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f2=xr.open_dataset(flist2.paths[1])\n",
    "f2.time_counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/results/forcing/atmospheric/GEM2.5/gemlam/gemlam_y2010m02d06.nc'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flist2.paths[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Resulting object does not have monotonic global indexes along dimension time_counter",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-d5718b8950db>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     55\u001b[0m         \u001b[0mjW\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0miW\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwopsdir\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwnam_fmt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbloomdrivers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetWindVarsYear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miyear\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m         \u001b[0mflist2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0met\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_model_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwopsdir\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mwnam_fmt\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mflen\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mftype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'None'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtres\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m24\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 57\u001b[0;31m         \u001b[0;32mwith\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_mfdataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mflist2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'paths'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mwinds\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     58\u001b[0m             \u001b[0mu_wind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwinds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mu_wind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mjW\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0miW\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     59\u001b[0m             \u001b[0mv_wind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwinds\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mv_wind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mjW\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0miW\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/py39/lib/python3.9/site-packages/xarray/backends/api.py\u001b[0m in \u001b[0;36mopen_mfdataset\u001b[0;34m(paths, chunks, concat_dim, compat, preprocess, engine, lock, data_vars, coords, combine, autoclose, parallel, join, attrs_file, **kwargs)\u001b[0m\n\u001b[1;32m    974\u001b[0m             \u001b[0;31m# Redo ordering from coordinates, ignoring how they were ordered\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    975\u001b[0m             \u001b[0;31m# previously\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 976\u001b[0;31m             combined = combine_by_coords(\n\u001b[0m\u001b[1;32m    977\u001b[0m                 \u001b[0mdatasets\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    978\u001b[0m                 \u001b[0mcompat\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompat\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/py39/lib/python3.9/site-packages/xarray/core/combine.py\u001b[0m in \u001b[0;36mcombine_by_coords\u001b[0;34m(datasets, compat, data_vars, coords, fill_value, join, combine_attrs)\u001b[0m\n\u001b[1;32m    787\u001b[0m             \u001b[0mindexes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconcatenated\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindexes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    788\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mindexes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_monotonic_increasing\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindexes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_monotonic_decreasing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 789\u001b[0;31m                 raise ValueError(\n\u001b[0m\u001b[1;32m    790\u001b[0m                     \u001b[0;34m\"Resulting object does not have monotonic\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    791\u001b[0m                     \u001b[0;34m\" global indexes along dimension {}\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Resulting object does not have monotonic global indexes along dimension time_counter"
     ]
    }
   ],
   "source": [
    "if recalc==True or not os.path.isfile(savepath):\n",
    "    basedir='/results2/SalishSea/nowcast-green.201905/'\n",
    "    nam_fmt='nowcast'\n",
    "    flen=1 # files contain 1 day of data each\n",
    "    ftype= 'ptrc_T' # load bio files\n",
    "    tres=24 # 1: hourly resolution; 24: daily resolution  \n",
    "    bio_time=list()\n",
    "    diat_alld=list()\n",
    "    no3_alld=list()\n",
    "    flag_alld=list()\n",
    "    cili_alld=list()\n",
    "    microzoo_alld=list()\n",
    "    mesozoo_alld=list()\n",
    "    intdiat=list()\n",
    "    intphyto=list()\n",
    "    spar=list()\n",
    "    intmesoz=list()\n",
    "    intmicroz=list()\n",
    "    grid_time=list()\n",
    "    temp=list()\n",
    "    salinity=list()\n",
    "    u_wind=list()\n",
    "    v_wind=list()\n",
    "    twind=list()\n",
    "    solar=list()\n",
    "    ik=0\n",
    "    for ind, datepair in enumerate(dateslist):\n",
    "        start=datepair[0]\n",
    "        end=datepair[1]\n",
    "        flist=et.index_model_files(start,end,basedir,nam_fmt,flen,ftype,tres)\n",
    "        flist3 = et.index_model_files(start,end,basedir,nam_fmt,flen,\"grid_T\",tres)\n",
    "        fliste3t = et.index_model_files(start,end,basedir,nam_fmt,flen,\"carp_T\",tres)\n",
    "        with xr.open_mfdataset(flist['paths']) as bio:\n",
    "            bio_time.append(np.array([pd.to_datetime(ii)+dt.timedelta(minutes=30) for ii in bio.time_counter.values]))\n",
    "            no3_alld.append(np.array(bio.nitrate.isel(y=ij,x=ii)) )\n",
    "            diat_alld.append(np.array(bio.diatoms.isel(y=ij,x=ii)))\n",
    "            flag_alld.append(np.array(bio.flagellates.isel(y=ij,x=ii)))\n",
    "            cili_alld.append(np.array(bio.ciliates.isel(y=ij,x=ii)))\n",
    "            microzoo_alld.append(np.array(bio.microzooplankton.isel(y=ij,x=ii)))\n",
    "            mesozoo_alld.append(np.array(bio.mesozooplankton.isel(y=ij,x=ii)))\n",
    "\n",
    "            with xr.open_mfdataset(fliste3t['paths']) as carp:\n",
    "                intdiat.append(np.array(np.sum(bio.diatoms.isel(y=ij,x=ii)*carp.e3t.isel(y=ij,x=ii),1))) # depth integrated diatom\n",
    "                intphyto.append(np.array(np.sum((bio.diatoms.isel(y=ij,x=ii)+bio.flagellates.isel(y=ij,x=ii)\\\n",
    "                                +bio.ciliates.isel(y=ij,x=ii))*carp.e3t.isel(y=ij,x=ii),1)))\n",
    "                spar.append(np.array(carp.PAR.isel(deptht=ik,y=ij,x=ii)))\n",
    "                intmesoz.append(np.array(np.sum(bio.mesozooplankton.isel(y=ij,x=ii)*carp.e3t.isel(y=ij,x=ii),1)))\n",
    "                intmicroz.append(np.array(np.sum(bio.microzooplankton.isel(y=ij,x=ii)*carp.e3t.isel(y=ij,x=ii),1)))\n",
    "\n",
    "        with xr.open_mfdataset(flist3['paths']) as grid:\n",
    "            grid_time.append(np.array([pd.to_datetime(ii)+dt.timedelta(minutes=30) for ii in grid.time_counter.values]))\n",
    "            temp.append(np.array(grid.votemper.isel(deptht=ik,y=ij,x=ii)) )#surface temperature\n",
    "            salinity.append(np.array(grid.vosaline.isel(deptht=ik,y=ij,x=ii))) #surface salinity\n",
    "        \n",
    "        jW,iW,wopsdir,wnam_fmt=bloomdrivers.getWindVarsYear(iyear)\n",
    "        flist2=et.index_model_files(start,end,wopsdir,wnam_fmt,flen=1,ftype='None',tres=24)\n",
    "        with xr.open_mfdataset(flist2['paths']) as winds:\n",
    "            u_wind.append(np.array(winds.u_wind.isel(y=jW,x=iW)))\n",
    "            v_wind.append(np.array(winds.v_wind.isel(y=jW,x=iW)))\n",
    "            twind.append(np.array(winds.time_counter))\n",
    "            solar.append(np.array(winds.solar.isel(y=jW,x=iW)))\n",
    "    \n",
    "    bio_time=np.concatenate(bio_time,axis=0)\n",
    "    diat_alld=np.concatenate(diat_alld,axis=0)\n",
    "    no3_alld=np.concatenate(no3_alld,axis=0)\n",
    "    flag_alld=np.concatenate(flag_alld,axis=0)\n",
    "    cili_alld=np.concatenate(cili_alld,axis=0)\n",
    "    microzoo_alld=np.concatenate(microzoo_alld,axis=0)\n",
    "    mesozoo_alld=np.concatenate(mesozoo_alld,axis=0)\n",
    "    intdiat=np.concatenate(intdiat,axis=0)\n",
    "    intphyto=np.concatenate(intphyto,axis=0)\n",
    "    spar=np.concatenate(spar,axis=0)\n",
    "    intmesoz=np.concatenate(intmesoz,axis=0)\n",
    "    intmicroz=np.concatenate(intmicroz,axis=0)\n",
    "    grid_time=np.concatenate(grid_time,axis=0)\n",
    "    temp=np.concatenate(temp,axis=0)\n",
    "    salinity=np.concatenate(salinity,axis=0)\n",
    "    u_wind=np.concatenate(u_wind,axis=0)\n",
    "    v_wind=np.concatenate(v_wind,axis=0)\n",
    "    twind=np.concatenate(twind,axis=0)\n",
    "    solar=np.concatenate(solar,axis=0)\n",
    "    \n",
    "    ### calculations based on saved values\n",
    "    no3_30to90m=np.sum(no3_alld[:,22:26]*e3t_0[:,22:26,ij,ii],1)/np.sum(e3t_0[:,22:26,ij,ii]) # average, considering cell thickness\n",
    "    sno3=no3_alld[:,0]\n",
    "    sdiat=diat_alld[:,0]\n",
    "    sflag=flag_alld[:,0]\n",
    "    scili=cili_alld[:,0]\n",
    "    intzoop=intmesoz+intmicroz\n",
    "    fracdiat=intdiat/intphyto # depth integrated fraction of diatoms\n",
    "    zoop_alld=microzoo_alld+mesozoo_alld\n",
    "    sphyto=sdiat+sflag+scili\n",
    "    phyto_alld=diat_alld+flag_alld+cili_alld\n",
    "    percdiat=sdiat/sphyto # fraction surface diatoms\n",
    "\n",
    "    # wind speed:\n",
    "    wspeed=np.sqrt(u_wind**2 + v_wind**2)\n",
    "    # wind direction in degrees from east\n",
    "    d = np.arctan2(v_wind, u_wind)\n",
    "    winddirec=np.rad2deg(d + (d < 0)*2*np.pi)\n",
    "    \n",
    "    allvars=(bio_time,diat_alld,no3_alld,flag_alld,cili_alld,microzoo_alld,mesozoo_alld,\n",
    "              intdiat,intphyto,spar,intmesoz,intmicroz,\n",
    "            grid_time,temp,salinity,u_wind,v_wind,twind,solar,\n",
    "            no3_30to90m,sno3,sdiat,sflag,scili,intzoop,fracdiat,zoop_alld,sphyto,phyto_alld,percdiat,\n",
    "            wspeed,winddirec)\n",
    "    pickle.dump(allvars,open(savepath,'wb'))\n",
    "else:\n",
    "    pvars=pickle.load(open(savepath,'rb'))\n",
    "    (bio_time,diat_alld,no3_alld,flag_alld,cili_alld,microzoo_alld,mesozoo_alld,\n",
    "              intdiat,intphyto,spar,intmesoz,intmicroz,\n",
    "            grid_time,temp,salinity,u_wind,v_wind,twind,solar,\n",
    "            no3_30to90m,sno3,sdiat,sflag,scili,intzoop,fracdiat,zoop_alld,sphyto,phyto_alld,percdiat,\n",
    "            wspeed,winddirec)=pvars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### loops that are not location specific (do not need to be redone for each location):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define sog region:\n",
    "fig, ax = plt.subplots(1,2,figsize = (6,6))\n",
    "with xr.open_dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/bathymetry_201702.nc') as bathy:\n",
    "    bath=np.array(bathy.Bathymetry)\n",
    "ax[0].contourf(bath,np.arange(0,250,10))\n",
    "viz_tools.set_aspect(ax[0],coords='grid')\n",
    "sogmask=np.copy(tmask[:,:,:,:])\n",
    "sogmask[:,:,740:,:]=0\n",
    "sogmask[:,:,700:,170:]=0\n",
    "sogmask[:,:,550:,250:]=0\n",
    "sogmask[:,:,:,302:]=0\n",
    "sogmask[:,:,:400,:]=0\n",
    "sogmask[:,:,:,:100]=0\n",
    "#sogmask250[bath<250]=0\n",
    "ax[1].contourf(np.ma.masked_where(sogmask[0,0,:,:]==0,bathy.Bathymetry),[0,100,250,550])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "k250=32 # approximate index for 250 m\n",
    "if recalc==True or not os.path.isfile(savepath2):\n",
    "\n",
    "    basedir='/results2/SalishSea/nowcast-green.201905/'\n",
    "    nam_fmt='nowcast'\n",
    "    flen=1 # files contain 1 day of data each\n",
    "    ftype= 'ptrc_T' # load bio files\n",
    "    tres=24 # 1: hourly resolution; 24: daily resolution  \n",
    "    flist=et.index_model_files(startjan,endmar,basedir,nam_fmt,flen,ftype,tres)\n",
    "    flist3 = et.index_model_files(startjan,endmar,basedir,nam_fmt,flen,\"grid_T\",tres)\n",
    "    fliste3t = et.index_model_files(startjan,endmar,basedir,nam_fmt,flen,\"carp_T\",tres)\n",
    "\n",
    "    ik=0\n",
    "    with xr.open_mfdataset(flist['paths']) as bio:\n",
    "        no3_past250m=np.array(np.sum(np.sum(np.sum(bio.nitrate.isel(deptht=slice(32,40))*sogmask[:,32:,:,:]*e3t_0[:,32:,:,:],3),2),1)\\\n",
    "                /np.sum(sogmask[0,32:,:,:]*e3t_0[0,32:,:,:]))\n",
    "        \n",
    "    # reading Fraser river flow files\n",
    "    dfFra=pd.read_csv('/ocean/eolson/MEOPAR/obs/ECRivers/Flow/FraserHopeDaily__Feb-8-2021_06_29_29AM.csv',\n",
    "                      skiprows=1)\n",
    "    # the original file contains both flow and water level information in the same field (Value)\n",
    "    # keep only the flow data, where PARAM=1 (drop PARAM=2 values, water level data)\n",
    "    # flow units are m3/s\n",
    "    # DD is YD, year day (ie. 1 is jan 1)\n",
    "    dfFra.drop(dfFra.loc[dfFra.PARAM==2].index,inplace=True)  \n",
    "\n",
    "    # rename 'Value' column to 'Flow' now that we have removed all the water level rows\n",
    "    dfFra.rename(columns={'Value':'Flow'}, inplace=True) \n",
    "        # inplace=True does this function on the orginal dataframe\n",
    "\n",
    "    # no time information so use dt.date\n",
    "    dfFra['Date']=[dt.date(iyr,1,1)+dt.timedelta(days=idd-1) for iyr, idd in zip(dfFra['YEAR'],dfFra['DD'])]\n",
    "    # taking the value from the yr column, jan1st date, and making jan1 column to be 1 not 0\n",
    "    dfFra.head(2)\n",
    "\n",
    "    # select portion of dataframe in desired date range\n",
    "    dfFra2=dfFra.loc[(dfFra.Date>=startjan.date())&(dfFra.Date<=endmar.date())]\n",
    "    riv_time=dfFra2['Date'].values\n",
    "    rivFlow=dfFra2['Flow'].values\n",
    "    # could also write dfFra['Date'], sometimes this is required\n",
    "    # newstart is a datetime object, so we convert it to just a date with .date\n",
    "    \n",
    "    allvars=(no3_past250m,riv_time,rivFlow)\n",
    "    pickle.dump(allvars,open(savepath2,'wb'))\n",
    "else:\n",
    "    pvars=pickle.load(open(savepath2,'rb'))\n",
    "    (no3_past250m,riv_time,rivFlow)=pvars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variables for bloom timing calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if recalc==True or not os.path.isfile(savepath3):\n",
    "    basedir='/results2/SalishSea/nowcast-green.201905/'\n",
    "    nam_fmt='nowcast'\n",
    "    flen=1 # files contain 1 day of data each\n",
    "    ftype= 'ptrc_T' # load bio files\n",
    "    tres=24 # 1: hourly resolution; 24: daily resolution  \n",
    "    flist=et.index_model_files(forbloomstart,forbloomend,basedir,nam_fmt,flen,ftype,tres)\n",
    "    flist2=et.index_model_files(forbloomstart,forbloomend,basedir,nam_fmt,flen,\"carp_T\",tres)\n",
    "\n",
    "    ik=0\n",
    "    with xr.open_mfdataset(flist['paths']) as bio:\n",
    "        bio_time0=np.array([pd.to_datetime(ii)+dt.timedelta(minutes=30) for ii in bio.time_counter.values])\n",
    "        sno30=np.array(bio.nitrate.isel(deptht=ik,y=ij,x=ii))\n",
    "        sdiat0=np.array(bio.diatoms.isel(deptht=ik,y=ij,x=ii))\n",
    "        sflag0=np.array(bio.flagellates.isel(deptht=ik,y=ij,x=ii))\n",
    "        scili0=np.array(bio.ciliates.isel(deptht=ik,y=ij,x=ii))\n",
    "        no3_alld0=np.array(bio.nitrate.isel(y=ij,x=ii)) \n",
    "        diat_alld0=np.array(bio.diatoms.isel(y=ij,x=ii))\n",
    "        flag_alld0=np.array(bio.flagellates.isel(y=ij,x=ii))\n",
    "        cili_alld0=np.array(bio.ciliates.isel(y=ij,x=ii))\n",
    "        with xr.open_mfdataset(flist2['paths']) as carp:\n",
    "            intdiat0=np.array(np.sum(bio.diatoms.isel(y=ij,x=ii)*carp.e3t.isel(y=ij,x=ii),1)) # depth integrated diatom\n",
    "            intphyto0=np.array(np.sum((bio.diatoms.isel(y=ij,x=ii)+bio.flagellates.isel(y=ij,x=ii)\\\n",
    "                            +bio.ciliates.isel(y=ij,x=ii))*carp.e3t.isel(y=ij,x=ii),1))\n",
    "    fracdiat0=intdiat0/intphyto0 # depth integrated fraction of diatoms\n",
    "\n",
    "    sphyto0=sdiat0+sflag0+scili0\n",
    "    phyto_alld0=diat_alld0+flag_alld0+cili_alld0\n",
    "    percdiat0=sdiat0/sphyto0 # percent diatoms\n",
    "\n",
    "    pickle.dump((bio_time0,sno30,sdiat0,sflag0,scili0,diat_alld0,no3_alld0,flag_alld0,cili_alld0,phyto_alld0,\\\n",
    "                 intdiat0,intphyto0,fracdiat0,sphyto0,percdiat0),open(savepath3,'wb'))\n",
    "else:\n",
    "    bio_time0,sno30,sdiat0,sflag0,scili0,diat_alld0,no3_alld0,flag_alld0,cili_alld0,phyto_alld0,\\\n",
    "                 intdiat0,intphyto0,fracdiat0,sphyto0,percdiat0=pickle.load(open(savepath3,'rb'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  *** Stop and check, have you made pickle files for all the years? ***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through years of spring time series (mid feb-june) for bloom timing\n",
    "years=list()\n",
    "bloomtime1=list()\n",
    "bloomtime2=list()\n",
    "bloomtime3=list()\n",
    "for year in range(2015,2020):\n",
    "    fname3=f'springBloomTime_{str(year)}_{loc}_{modver}.pkl'\n",
    "    savepath3=os.path.join(savedir,fname3)\n",
    "    bio_time0,sno30,sdiat0,sflag0,scili0,diat_alld0,no3_alld0,flag_alld0,cili_alld0,phyto_alld0,\\\n",
    "                 intdiat0,intphyto0,fracdiat0,sphyto0,percdiat0=pickle.load(open(savepath3,'rb'))\n",
    "    # put code that calculates bloom timing here\n",
    "    bt1=bloomdrivers.metric1_bloomtime(phyto_alld0,no3_alld0,bio_time0)\n",
    "    bt2=bloomdrivers.metric2_bloomtime(sphyto0,sno30,bio_time0)\n",
    "    bt3=bloomdrivers.metric3_bloomtime(sphyto0,sno30,bio_time0)\n",
    "    years.append(year)\n",
    "    bloomtime1.append(bt1)\n",
    "    bloomtime2.append(bt2)\n",
    "    bloomtime3.append(bt3)   \n",
    "years=np.array(years)\n",
    "bloomtime1=np.array(bloomtime1)\n",
    "bloomtime2=np.array(bloomtime2)\n",
    "bloomtime3=np.array(bloomtime3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([Timestamp('2015-05-19 12:30:00'), Timestamp('2016-06-05 12:30:00'),\n",
       "       Timestamp('2017-04-24 12:30:00'), Timestamp('2018-05-26 12:30:00'),\n",
       "       Timestamp('2019-03-28 12:30:00')], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bloomtime1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combine separate year files into arrays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through years (for location specific drivers)\n",
    "\n",
    "years=list()\n",
    "windjan=list()\n",
    "windfeb=list()\n",
    "windmar=list()\n",
    "solarjan=list()\n",
    "solarfeb=list()\n",
    "solarmar=list()\n",
    "parjan=list()\n",
    "parfeb=list()\n",
    "parmar=list()\n",
    "tempjan=list()\n",
    "tempfeb=list()\n",
    "tempmar=list()\n",
    "saljan=list()\n",
    "salfeb=list()\n",
    "salmar=list()\n",
    "zoojan=list()\n",
    "zoofeb=list()\n",
    "zoomar=list()\n",
    "mesozoojan=list()\n",
    "mesozoofeb=list()\n",
    "mesozoomar=list()\n",
    "microzoojan=list()\n",
    "microzoofeb=list()\n",
    "microzoomar=list()\n",
    "intzoojan=list()\n",
    "intzoofeb=list()\n",
    "intzoomar=list()\n",
    "intmesozoojan=list()\n",
    "intmesozoofeb=list()\n",
    "intmesozoomar=list()\n",
    "intmicrozoojan=list()\n",
    "intmicrozoofeb=list()\n",
    "intmicrozoomar=list()\n",
    "midno3jan=list()\n",
    "midno3feb=list()\n",
    "midno3mar=list()\n",
    "\n",
    "for year in range(2015,2020):\n",
    "    fname=f'JanToMarch_TimeSeries_{year}_{loc}_{modver}.pkl'\n",
    "    savepath=os.path.join(savedir,fname)\n",
    "    bio_time,diat_alld,no3_alld,flag_alld,cili_alld,microzoo_alld,mesozoo_alld,\\\n",
    "            intdiat,intphyto,spar,intmesoz,intmicroz,grid_time,temp,salinity,u_wind,v_wind,twind,\\\n",
    "            solar,no3_30to90m,sno3,sdiat,sflag,scili,intzoop,fracdiat,zoop_alld,sphyto,phyto_alld,\\\n",
    "            percdiat,wspeed,winddirec=pickle.load(open(savepath,'rb'))\n",
    "    # put code that calculates drivers here\n",
    "    wind=bloomdrivers.janfebmar_wspeed3(twind,wspeed)\n",
    "    solar=bloomdrivers.janfebmar_irradiance(twind,solar)\n",
    "    par=bloomdrivers.janfebmar_spar(bio_time,spar)\n",
    "    temp=bloomdrivers.janfebmar_temp(grid_time,temp)\n",
    "    sal=bloomdrivers.janfebmar_temp(grid_time,salinity)\n",
    "    zoo=bloomdrivers.janfebmar_zooplankton(bio_time,zoop_alld)\n",
    "    mesozoo=bloomdrivers.janfebmar_mesozooplankton(bio_time,mesozoo_alld)\n",
    "    microzoo=bloomdrivers.janfebmar_microzooplankton(bio_time,microzoo_alld)\n",
    "    intzoo=bloomdrivers.janfebmar_depth_intzoop(bio_time,intzoop)\n",
    "    intmesozoo=bloomdrivers.janfebmar_depth_intmesozoop(bio_time,intmesoz)\n",
    "    intmicrozoo=bloomdrivers.janfebmar_depth_intmicrozoop(bio_time,intmicroz)\n",
    "    midno3=bloomdrivers.janfebmar_mid_depth_no3(bio_time,no3_30to90m)\n",
    "    \n",
    "    years.append(year)\n",
    "    windjan.append(wind[0])\n",
    "    windfeb.append(wind[1])\n",
    "    windmar.append(wind[2])   \n",
    "    solarjan.append(solar[0])\n",
    "    solarfeb.append(solar[1])\n",
    "    solarmar.append(solar[2])\n",
    "    parjan.append(par[0])\n",
    "    parfeb.append(par[1])\n",
    "    parmar.append(par[2])\n",
    "    tempjan.append(temp[0])\n",
    "    tempfeb.append(temp[1])\n",
    "    tempmar.append(temp[2])\n",
    "    saljan.append(sal[0])\n",
    "    salfeb.append(sal[1])\n",
    "    salmar.append(sal[2])\n",
    "    zoojan.append(zoo[0])\n",
    "    zoofeb.append(zoo[1])\n",
    "    zoomar.append(zoo[2])\n",
    "    mesozoojan.append(mesozoo[0])\n",
    "    mesozoofeb.append(mesozoo[1])\n",
    "    mesozoomar.append(mesozoo[2])\n",
    "    microzoojan.append(microzoo[0])\n",
    "    microzoofeb.append(microzoo[1])\n",
    "    microzoomar.append(microzoo[2])\n",
    "    intzoojan.append(intzoo[0])\n",
    "    intzoofeb.append(intzoo[1])\n",
    "    intzoomar.append(intzoo[2])\n",
    "    intmesozoojan.append(intmesozoo[0])\n",
    "    intmesozoofeb.append(intmesozoo[1])\n",
    "    intmesozoomar.append(intmesozoo[2])\n",
    "    intmicrozoojan.append(intmicrozoo[0])\n",
    "    intmicrozoofeb.append(intmicrozoo[1])\n",
    "    intmicrozoomar.append(intmicrozoo[2])\n",
    "    midno3jan.append(midno3[0])\n",
    "    midno3feb.append(midno3[1])\n",
    "    midno3mar.append(midno3[2])\n",
    "\n",
    "years=np.array(years)\n",
    "windjan=np.array(windjan)\n",
    "windfeb=np.array(windfeb)\n",
    "windmar=np.array(windmar)\n",
    "solarjan=np.array(solarjan)\n",
    "solarfeb=np.array(solarfeb)\n",
    "solarmar=np.array(solarmar)\n",
    "parjan=np.array(parjan)\n",
    "parfeb=np.array(parfeb)\n",
    "parmar=np.array(parmar)\n",
    "tempjan=np.array(tempjan)\n",
    "tempfeb=np.array(tempfeb)\n",
    "tempmar=np.array(tempmar)\n",
    "saljan=np.array(saljan)\n",
    "salfeb=np.array(salfeb)\n",
    "salmar=np.array(salmar)\n",
    "zoojan=np.array(zoojan)\n",
    "zoofeb=np.array(zoofeb)\n",
    "zoomar=np.array(zoomar)\n",
    "mesozoojan=np.array(mesozoojan)\n",
    "mesozoofeb=np.array(mesozoofeb)\n",
    "mesozoomar=np.array(mesozoomar)\n",
    "microzoojan=np.array(microzoojan)\n",
    "microzoofeb=np.array(microzoofeb)\n",
    "microzoomar=np.array(microzoomar)\n",
    "intzoojan=np.array(intzoojan)\n",
    "intzoofeb=np.array(intzoofeb)\n",
    "intzoomar=np.array(intzoomar)\n",
    "intmesozoojan=np.array(intmesozoojan)\n",
    "intmesozoofeb=np.array(intmesozoofeb)\n",
    "intmesozoomar=np.array(intmesozoomar)\n",
    "intmicrozoojan=np.array(intmicrozoojan)\n",
    "intmicrozoofeb=np.array(intmicrozoofeb)\n",
    "intmicrozoomar=np.array(intmicrozoomar)\n",
    "midno3jan=np.array(midno3jan)\n",
    "midno3feb=np.array(midno3feb)\n",
    "midno3mar=np.array(midno3mar)\n",
    "\n",
    "# get year day\n",
    "yearday1=et.datetimeToYD(bloomtime1)  # convert to year day tool\n",
    "yearday2=et.datetimeToYD(bloomtime2)\n",
    "yearday3=et.datetimeToYD(bloomtime3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through years (for non-location specific drivers)\n",
    "\n",
    "fraserjan=list()\n",
    "fraserfeb=list()\n",
    "frasermar=list()\n",
    "deepno3jan=list()\n",
    "deepno3feb=list()\n",
    "deepno3mar=list()\n",
    "\n",
    "for year in range(2015,2020):\n",
    "    fname2=f'JanToMarch_TimeSeries_{year}_{modver}.pkl'\n",
    "    savepath2=os.path.join(savedir,fname2)\n",
    "    no3_past250m,riv_time,rivFlow=pickle.load(open(savepath2,'rb'))\n",
    "    # put code that calculates drivers here\n",
    "    fraser=bloomdrivers.janfebmar_fraserflow(riv_time,rivFlow)\n",
    "    deepno3=bloomdrivers.janfebmar_deepno3(riv_time,no3_past250m)\n",
    " \n",
    "    fraserjan.append(fraser[0])\n",
    "    fraserfeb.append(fraser[1])\n",
    "    frasermar.append(fraser[2])\n",
    "    deepno3jan.append(deepno3[0])\n",
    "    deepno3feb.append(deepno3[1])\n",
    "    deepno3mar.append(deepno3[2])\n",
    "\n",
    "fraserjan=np.array(fraserjan)\n",
    "fraserfeb=np.array(fraserfeb)\n",
    "frasermar=np.array(frasermar)\n",
    "deepno3jan=np.array(deepno3jan)\n",
    "deepno3feb=np.array(deepno3feb)\n",
    "deepno3mar=np.array(deepno3mar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bloom date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f6579a0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot bloomtime for each year: \n",
    "fig,ax=plt.subplots(1,1,figsize=(7,5))\n",
    "p1=ax.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p2=ax.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p3=ax.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax.set_ylabel('Year Day')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Spring Phytoplankton Bloom Date by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average wind speed cubed (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f53b160>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LFzdLA93FF19c/Omnn3oDLFmyxPeaa6452nuzpKTEcN1110V369atS5cuXRI++ugj76qqKjV9+vTQFStW+MTHxycsXLjQZ9KkSaE33nhj1IABA2JGjx7dYeXKlR71rcbFxcWGa6+9Njo2NjYhNjY2YdGiRd6W65ZHRUWdNGQfT5sJvq6uruZvvvnmwJ49e/auW7cuadq0aeFmsxmAlJQU54ceeijnwIEDu728vEwffPCBz4nOFRoaatywYUPSnj179i5btuzQxIkTI+v37dixw+2ll15KP3jw4O7x48fnLVmyxA/AZDLx1Vdf+dxzzz35x55v8eLF3kOGDCnu0aNHtbe3t2njxo2uV199dcm2bdvcSkpKDABLlizxufbaawsyMzPt//e//4WsX78+ac+ePXvPO++8iv/+979B9edydnY2b926NXHs2LGFN998c+GuXbv2JiYm7omLi6ucO3euP8ADDzwQMX78+Jxdu3btDQ0NPfrN/+KLLzwPHDjgvGPHjr179+7d89dff7l+99137mf41gshmlFlZuYpbRdCCCGEOFVHFi/23f3CC1HVOTmOaE11To7j7hdeiGqO8HvrrbcWLFu2zKeiokLt3bvXtV+/fuX1+6ZNmxYydOjQkl27du3dsGFD4pNPPhleU1Ojpk6dmjFq1KjCffv27RkzZkwhwI4dO1xXrVp1YMWKFYcbnn/KlCkhnp6epqSkpD1JSUl7LrvsstIzrRlOPrnVUXctvytiV84u1+a4aL1ugd0q3r3y3RM2adczm81qwoQJ4Zs3b3Y3GAzk5OQ4pqWl2QOEhYVV9+/fvxLg3HPPrThy5IjTic5VU1Oj7r777qg9e/a4GAwGkpOTjx7fo0eP8vj4+BqAuLi4Gm9vb+OmTZtcMjMzHbp27VoRHBz8j5nYPvnkE9+HH344B+Caa64p+PDDD30HDhxYMWTIkJKlS5d63XnnnYU//vij1+uvv572/fffexw8eNC5T58+8QC1tbWqV69eZfXnuu222wrrv966davLU089FVZaWmpXXl5uN3jw4GKAbdu2ua9evfoAwD333JP/zDPPhAN8//33nuvXr/dMSEhIAKioqDDs27fPeeTIkWUIIVoFl5CQum7Ox3D0CKQmuxrHoBP++hJCCCGEOKmk118PM1dX/62R01xdbUh6/fWw6JtvPqP5dfr27VuZlpbmtHDhQt9hw4YVN9z3888/e65atcp77ty5wQDV1dXqwIEDja5LOmLEiCJ3d/d/TNa1fv16z6VLlx6d/DYgIOBMZsI+qs2sETN//nzf/Px8+507d+51cnLSYWFh3SsrKw0Ajo6OR98wOzs7Xb/d3t5em0x171NFRYWqP+aFF14ICgwMrP38888Pm81mXFxcetXvc3V1NTe87p133pn39ttv++fk5Djceeed/2jtzcrKstu8ebNnUlKSywMPPIDJZFJKKf3WW2+l3XDDDQVvvPFGoL+/v6lHjx4VPj4+Zq01AwcOLDn2zkY9Dw+Po9cfO3Zsh88+++xAv379KufOneu3bt06jxO9R1prJkyYkPnoo4/mneTtFEJYSeSV95G04Hm0qfroNoOjM/5dbiP5xUN49vXGb0QA9p5t5tezEEIIIVqZ6tzcRsPm8bafqhEjRhQ9/fTTEatXr07Myck5+qFFa81nn312oGfPntUNj9+4caPbsedwc3MzH7ut/hx1C8c0ryZ/smpqy+zZUlxcbOfv71/r5OSkV6xY4ZGRkXHSb1pERET177//7jZ06NCKxYsXH+3+XFxcbBceHl5jZ2fH66+/7lcfjhtz6623Fr3wwgthRqNRXXPNNf9YdufDDz/0GT16dP7HH3+cXL+td+/ecatXr3a/7LLLSsePHx+9cOFC/+uuu64AYMiQIeWPPPJI5K5du5y6detWXVpaajh8+LBDjx49qo89d0VFhSEyMrK2urpaLV261DckJKQW4JxzzilbtGiRz5gxYwrffffdo90VRo4cWfLMM8+Ejh07tsDLy8t8+PBhB0dHRx0WFtY2ZsoSwsZVpVRiyDqPyBGTydn2HpWZmbiEhBA/eTLBF19Gweo8ijcVUrq1GJ+L/PAZ4ofBqc2MSBFCCCFEK+EUEFBTnZPzj7zkFBBQ0xznv++++/K8vLxMffr0qVy5cuXRxrmhQ4eWzJ49O2jRokUpBoOBTZs2uQwYMKDS09PTVFZW1qQPNUOGDCmZM2dO4Lvv1uXP3Nxcu+Zo9W31n6hqa2txdHTU99xzT8H27dvdunXr1uWjjz7y7dChQ9XJnjtlypTsd955J+Dcc8+Nz8vLOxryJ0yYkLNkyRK/nj17xiclJTm7uLg0ercBwNnZWffv37/kiiuuKLC3/+d9gk8//dRv9OjRhQ23XXnllYUffvihr729PRdffHHxunXrvK6//vpiqBtfPH/+/CM33HBDx9jY2IRevXrF79y5s9ElkKZMmZLRp0+fLoMGDYqNiYk5+npfe+211Ndeey2oe/fuXTIzMx3c3d1NAKNHjy657rrrCnr37h0fGxubcPXVV3cqKiqyO9n7JIQ4+0zlRjIXpWPnaUfX/93GsA0bGHXgAMM2bCD8yiuxd7cncHQwUVM64RbvTsH3eRz530GKNxeizbJknxBCCCGaLvaBB9INTk5/yzgGJydz7AMPpDfH+Tt16lT7n//8J+fY7TNmzMgwGo0qPj4+ISYmpuuTTz4ZBjBy5MjSpKQkl/rJrU507unTp2cWFRXZxcTEdI2Li0v49ttvPQDGjRsXHhQU1KOqqsoQFBTUY9KkSac0ka/S+vgfqLZv336kZ8+eVu02++uvv7qMHTs2eufOnac9dfWZMJlMdO3aNeHTTz892L1793+0ylpDaWmpwc3NzWwwGFiwYIHPsmXLfH/44YeDzXHu7du3+/fs2TO6Oc7VnNzc3HR5efnJDxSiFdJmTcbCVCr3VxD+UBTOkS4nfU7l4Qryvs6h6kgljsFO+I8KxLWL21np+iOEEEKIOkqpCq31P7rltganms2OLF7sm/T662HVubmOTgEBNbEPPJB+puN7W7sTZZlWPYjsxRdfDJg/f37gSy+9ZJVu1lu3bnW+8sorY0aOHFnYWkIvwKZNm1wffvjhSK01np6epkWLFh2xdk1CiOMrWJNHxb5yAq4NblLoBXDp4Er4Q1GU7Sglf2UOGQtTcYlxxX9UIM4RTTuHEEIIIdqv6JtvLrD1oHsqWn2Lr2hZ0uIrRPMq31dGxoJUPHp5EXRTyGm12GqjpviXQvJX52EuN+HRyxO/ywJx8HE4CxULIYQQ7Zcttfi2R222xVcIIdqy2oJasj7MwDHYicDrgk+7m7KyV3hf6ItHby8Kf8inaH0BZdtL8b7QF59hfti5yFB+IYQQQogTkeArhBBngdloJnNRGpg1IXeGY3A887kE7Vzs8L88EK8BPuR/m0vhT/kU/1aE7yX+eA/wQdnL+F8hhBBCiMa0+lmdhRCiLcr7Mpvq1CqCbgrFMaBZlsw7ysHHgeCbQ4mY1AGnUCfyvsomeeZBSv8q4UTDV4QQQggh2isJvkII0cxK/iii+JcifC7yw727x8mfcJqcw50Juy+S0LERKAcDWe+nk/ZqMpWHKs7aNYUQQggh2qJWH3zt7Ox6xcfHJ9T/SUxMPG7TSZ8+feLWr1/v2pL1nUxtbS0+Pj4977///jBr1yKEOPuqM6rI+TQLl86u+P0r4KxfTymFWxd3Iid3IPD6EGoLa0l7LZmMd9OoyWk1k9ELIYQQwgYopXpdddVVHeof12edoUOHdj7R83755ReXZcuWeR1v//r1613vuOOOiOPtLy0tNQwZMqRzhw4dunbu3Lnr+PHjTzlbtfrg6+TkZN63b9+e+j9xcXE1Z3K+2traM67JaDQ2+dgvvvjCq0OHDtVff/21j9lsPvkTTqI56hdCnB2mShOZ76VhcLEj+LYwlF3LjblVBoXXBd5ET+uE38gAKpLKSZ55iJzPszCWNf13lhBCCCHE8bi4uJgTExNdysrKFMCXX37pGRQUdNKAsmXLFtdvvvmm0eBbW1vLhRdeWLFo0aITLmH7yCOPZB8+fHj3rl279vz222/un3zyieep1N7qg29jNmzY4Nq7d++4rl27dhk4cGBMcnLy0TU9Fi1a5HfuuefGx8TEdP3pp59cASZNmhR64403Rg0YMCBm9OjRHebOnet32223RdY/Z+jQoZ1XrlzpAXDzzTdHduvWrUvnzp27Tpw4MbT+mLCwsO6TJ08O6dWrV9wTTzwRnJCQ0KV+386dO526du169HFDS5Ys8R0/fnx2aGhozY8//uhmMpkICwvrnpeXd3Qa1sjIyG6pqan2GRkZ9pdeemmnbt26denWrVuX1atXuzVWf2JiomOvXr3iEhISuiQkJHRZs2aNG4DJZOKWW26J7Ny5c9ehQ4d2Hjx4cOf33nvP52TvmRDizGmtyf44g9qCWkJuD8PewzpzBxqcDPgO9yf6iU54XeBN8S+FJD9/kII1eZhrzvzmmxBCCCHahnnz8A0NpbvBQK/QULrPm4dvc5z34osvLv7000+9oS7rXHPNNUfXCi4pKTFcd9110d26devSpUuXhI8++si7qqpKTZ8+PXTFihU+8fHxCQsXLvQ5Nt+sXLnSo77VuLi42HDttddGx8bGJsTGxiYsWrTI28PDwzxq1KhSAGdnZ92jR4+K1NTUU5pEpdUH3+rqakN9N+dLLrmkU3V1tXrooYcily9ffnD37t17b7/99rzJkycfbequqKgwbNu2bd/cuXOTx44de7QZfseOHa6rVq06sGLFisMnut6cOXPSd+3atXffvn27N23a5PHbb7+51O9zdnY2b926NXHmzJlZHh4epl9++cUFYP78+f433XRT/rHnKisrU7/88ovH9ddfX3zdddcVfPTRR752dnYMHz68aPHixd4AP/74o1t4eHhNRESE8d57742YNGlS9q5du/Z++eWXB8eNGxfdWP2hoaHGDRs2JO3Zs2fvsmXLDk2cODES4IMPPvBJTU11TExM3P3+++8f2bZtm7vlPTzheyaEOHOFPxZQvqsM/yuCcOlo/REX9h72BF4XQtRjHXGJcSX/21ySpx+k5PcitFkmwBJCCCFs2bx5+E6cSFRmJo5aQ2YmjhMnEtUc4ffWW28tWLZsmU9FRYXau3eva79+/crr902bNi1k6NChJbt27dq7YcOGxCeffDK8pqZGTZ06NWPUqFGF+/bt2zNmzJhCOH4+mzJlSoinp6cpKSlpT1JS0p7LLrustOH+vLw8uzVr1niPHDmy5FTqbnKTxF379kXsKi9v1k9z3dzcKt6Njz9hk3Z9V+f6x3/88Yfz/v37XS666KJYALPZTEBAwNHm9ZtuuqkAYOTIkWVlZWWG+pbVESNGFLm7u5/0097777/vu2jRIn+j0ahyc3Mdtm/f7ty3b99KgNtuu62w/rg77rgjb+HChf59+vRJXb58uc8ff/yx99hzffLJJ94XXHBBqYeHh/mWW24pPOecc0KNRmPqTTfdVPDcc8+FPvzww/mLFy8+epdk06ZNnvv37z8atMvKyuwKCwsNx9ZfU1Oj7r777qg9e/a4GAwGkpOTnQA2bNjgPnr06EI7OzsiIyONF1xwQSnAjh07nE70ngkhzkzF/nLyv8nB/RwPvC/0sXY5f+MY5ETo3RFUHqwg9+tsspdkUriuAP8rAnGLc7d2eUIIIYQ4C557jrCqqr83clZVYXjuOcLGjaPgeM9rir59+1ampaU5LVy40HfYsGHFDff9/PPPnqtWrfKeO3duMNQ1wB04cKDRltnj5bP169d7Ll269FD944CAAFP917W1tYwePbrj2LFjsxMSEk5pCGybW8dXa606d+5c+ddff+1rbL9SqtHHbm5uR/v42dvb64bjbaurqw0A+/btc3z99deDtm7dujcgIMB0zTXXRFdVVR39B+Ph4XH0SbfffnvhzJkzQ5cuXVravXv3iuDg4KPfkHpLly713bp1q3tYWFh3gOLiYruVK1d6XHHFFaV33323U0ZGhv3333/v/cILL2RYXhtbtmzZ29g/gIb1v/DCC0GBgYG1n3/++WGz2YyLi0uv+uefznsmhDh9xqJasj5IxyHAkaDrQ/7xO6i1cOnkSsTD0ZT9VULeN7lkzEvFNd4N/1GBOIU6W7s8IYQQQjSjrCwaDZvH236qRowYUfT0009HrF69OjEnJ+doptRa89lnnx3o2bPn32bY3Lhxo9ux52iYbxrSWh/389RNN90U3bFjx6qnnnoq51RrbnLwPVnLbEvp0aNHVUFBgf3atWvdhg0bVl5dXa127tzpdP7551cBLFmyxGfUqFGlq1atcvfw8DD5+fn9I5B26tSpZuHCha4mk4nDhw877Nixww2gsLDQzsXFxezr62tKTU21//nnn70GDx5ceuzzAVxdXfXgwYOLJ02aFPn6668fOXZ/QUGBYcuWLe7p6ek7XFxcNMCrr77q9/HHH/teddVVpSNHjiwaP358ROfOnSvrQ/PAgQNLZs6cGfjf//43G+pmP+vfv3/lsecuLi62Cw8Pr7Gzs+P111/3M5nqXuKgQYPKPvzwQ78HHnggPyMjw/63337zuPHGGwtO9p4JIU6PNmky30/HXGMm7P4oDM52J3+SFSmDwuM8L9x6eFC8sZCCNXmkzDqMZ28v/EYGYO8tQ/+FEEIIWxAcTE1m5j9DbnAwZzRRcL377rsvz8vLy9SnT5/K+rmSAIYOHVoye/bsoEWLFqUYDAY2bdrkMmDAgEpPT09TWVlZk4bZDhkypGTOnDmB7777bipAbm6uXUBAgOmhhx4KLSkpsVu6dOmR06m51Y/xPZazs7NeunTpwSlTpoTHxcUldO3aNWHdunVH++v5+PiYzj333PgHHnggav78+UcaO8cll1xSFhERUR0XF9f14YcfjkhISKgA6NevX2W3bt0qYmJiut56663RvXr1KjtRLbfddlsBwOjRo//Rv/yjjz7y6d+/f2l96AW44YYbitasWeNdWVmpbr755oLly5f7XnvttUe7Ty9YsCD1zz//dIuNjU3o1KlT19dff73RtVAmTJiQs2TJEr+ePXvGJyUlObu4uJihrhU6JCSkJjY2tuudd94Z1bNnz3Jvb2/Tyd4zIcTpyfs6h6ojlQTdEIpTsJO1y2kyg70BnyF+RD/RGe/BvpRuLeHI/w6S920Opqp/3CsUQgghRBvz1FOkOzvztxZVZ2fMTz1FenOcv1OnTrX/+c9//tHqOmPGjAyj0aji4+MTYmJiuj755JNhACNHjixNSkpyqZ/c6kTnnj59emZRUZFdTExM17i4uIRvv/3W4+DBgw6vvfZayP79+527du2aEB8fnzBnzhz/U6lZHa97LMD27duP9OzZM+9UTtiePPXUU0HFxcV2r776aoa1a6lXXFxs8PLyMmdlZdn17t27y6ZNm/ZFRkY2eS2T7du3+/fs2TP6LJZ4Wtzc3HR5efnJDxSihZRuKyHrg3S8L/Qh4Opga5dzRmrza8j7NpeyP0uwc7fD91J/vPr5tOhyTEIIIURroJSq0Fr/o1tua3Cq2WzePHyfe46wrCwcg4Opeeop0s90fG9rd6Is0+bG+LYWl1xySafk5GSndevWJVm7loYuueSSmJKSErva2lr16KOPZp5K6BVCNE1NdjXZSzNwjnbBf1SQtcs5Yw5+joTcGkbVYF/yvs4h9/NsitYX4j8qELdu7q123LIQQgghjm/cOApsPeieCgm+p2nNmjUHrV1DY37//fdEa9cghC0zV5nIeDcNg6OBkNvDUPa2EwqdI10Iuz+S8t1l5K3IIfPdNJw7uBBwZRDOUS4nP4EQQgghRCslwVcIIZpIa032J1nU5tYQdl+kTU4GpZTCvZsHbl3cKfmtiPzvc0l95Qju53jgf1kgDv7NMhmkEEIIIUSLkuArhBBNVLS+kLJtJfhdHoBrTKsc/tNslJ3Cq78PHud5UvhTAYU/51O2sxTvAb74DvfDzk3++xBCCCFE2yGfXIQQogkqD1WQ93U2bt3c8bnIz9rltBiDsx1+IwPw6u9N/vd5FG0ooOT3Inwv8cdrkA8Ghza3OIAQQggh2iH5xCKEECdhLDWS+UE6Dr4OBN0U2i4ne7L3ciDo+hAiH+2AcwcX8lbkkDz9ECVbi9Hm468OIIQQQgjRGrT64KuU6nXVVVd1qH9cW1uLj49Pz6FDh3ZujvO7urqe29RjL7744k7nnHNOfHNc11YopSKUUj8ppfYqpXYrpR62bPdVSq1RSu23/O3T4DlTlVIHlFKJSqlLrVe9ECenTZqsD9IxV5gIuSMcOxc7a5dkVU4hzoSNjSTsvkjsXA1kf5RB6stHqNgvy40JIYQQtu50s9kvv/zismzZMq/j7V+/fr3rHXfcEXGicwwaNCgmLi4uoXPnzl1vuummSKPx1BavafXB18XFxZyYmOhSVlamAL788kvPoKCg2lM5R23tKR3eqLy8PLvdu3e7lZSU2O3bt++MZ3c51W9UK2YEHtFadwEuAO5XSiUAU4AftNYxwA+Wx1j23QB0BUYAbyql2neSEK1a/re5VB6oIPC6YJzCnK1dTqvhGutGxKQOBN0ciqncSPqbKaQvTKU6q9rapQkhhBDiLDndbLZlyxbXb775ptHgW1tby4UXXlixaNGi1BOdY/ny5QcTExP3JCUl7c7Pz3d49913fU50/LFaffAFuPjii4s//fRTb4AlS5b4XnPNNUfXo/rpp59czz333PguXboknHvuufHbt293Apg7d67fyJEjO1500UWdBw0aFFtcXGy49tpro2NjYxNiY2MTFi1a5F1/jgcffDAsLi4uoWfPnvGpqamNjnv+8MMPfYYNG1Z09dVXF7z//vu+AJdddlnHhncurrnmmuhFixZ5G41G7r333vBu3bp1iY2NTXjppZf8AVauXOnRt2/f2FGjRnWIi4vrCjBs2LBOXbt27dK5c+eus2bN8q8/18svv+wfHR3drU+fPnE33HBD1G233RYJkJGRYX/ppZd26tatW5du3bp1Wb16tVVn2NFaZ2qt/7R8XQrsBcKAK4H3LYe9D1xl+fpKYKnWulprfRg4APRp0aKFaKKynaUU/piPZz9vPHt7W7ucVkcZFJ7nexE1pRN+lwdQdaiClBcPkf1JJsbiM7/hKIRondKWL2ftoEGs6NyZtYMGkbZ8ubVLEkI0Zv88X74I7c7Hhl58Edqd/fN8m+O0J8pmJSUlhuuuuy66W7duXbp06ZLw0UcfeVdVVanp06eHrlixwic+Pj5h4cKFPpMmTQq98cYbowYMGBAzevToDitXrvSobzU+Xm7z9fU1A9TW1qra2lp1qkPP2kTwvfXWWwuWLVvmU1FRofbu3evar1+/o33qevbsWfX777/v27t3756nn346/bHHHguv3/fnn3+6L1my5PDmzZuTpkyZEuLp6WlKSkrak5SUtOeyyy4rBaisrDT069evLDExcU+/fv3KXnvttYDGavj00099b7nlloLbb7+94PPPP/cFuP766wuWLVvmA1BVVaU2bdrkee211xa/8sor/l5eXqZdu3bt3b59+973338/oL6VeMeOHW4vvfRS+sGDB3cDLF68+Mju3bv3/vXXX3vmz58flJWVZXfkyBGHWbNmhfz22297N2zYkLR///6jzUz33ntvxKRJk7J37dq198svvzw4bty46LPwlp8WpVQ0cC7wGxCktc6EunAMBFoOCwMa3s1Js2wTolWpya0h++MMnCKcCbg6yNrltGoGRwO+F/sT/UQnvAf6UPJbEUf+d5D873MxV5utXZ4QohmlLV/OjieeoDIjA7SmMiODHU88IeFXiNZm/zxftk6MoirTETRUZTqydWJUc4TfE2WzadOmhQwdOrRk165dezds2JD45JNPhtfU1KipU6dmjBo1qnDfvn17xowZUwiwY8cO11WrVh1YsWLF4YbnP15uAxg4cGBMQEBATzc3N9Odd95ZeCp1N3lW5+wlGRHVWdWup3Lyk3EKdqoIujH0hE3aAH379q1MS0tzWrhwoe+wYcOKG+4rKCiwu/766zscOXLEWSmla2trj0b/QYMGlQQFBZkA1q9f77l06dJD9fsCAgJMAA4ODvqGG24oBujVq1f52rVrPY+9fmpqqn1ycrLT8OHDywwGA/b29vqPP/5wvvbaa4sfe+yxyMrKSvX555979enTp9Td3V2vXbvWc9++fa5ff/21D0Bpaandnj17nB0dHXWPHj3K4+Pja+rPPXPmzKBvvvnGGyArK8th9+7dzhkZGQ59+/Ytra/96quvLkxKSnIG2LRpk+f+/ftd6p9fVlZmV1hYaPDx8bHqp0ullDvwOTBBa11ygjswje1odGYcpdRYYCyAo6OsHSpajrnGTOaiNDAoQu4Il5mLm8jO3Z6A0cF4DfIl/5scClblUfxLIX4jA/Ds442ya3+Tgglha/bNmoWpsvJv20yVleybNYvwK6+0UlVCiH/Y+VwY5qq/f4AxVxnY+VwYMeMKjvOsJjlRNvv55589V61a5T137txggOrqanXgwIFGP8iPGDGiyN3d/R854Hi5DWDjxo37Kyoq1NVXX91xxYoVnldffXVJU+tuM8sZjRgxoujpp5+OWL16dWJOTs7Ruh9//PGwwYMHl65Zs+ZgYmKi40UXXRRXv8/V1fVoGNRaNzoTq729vTYYDPVfYzQa/3HQ+++/71tSUmIXERHRHerC5ocffug7d+7cjAsuuKD0iy++8Fy2bJnPjTfeWGC5lpo9e3bKNddc87dvxMqVKz0a1rRy5UqPdevWeWzZsmWfh4eHuU+fPnGVlZUGrY8/Q6rWmi1btuxt7B+JtSilHKgLvYu11l9YNmcrpUK01plKqRAgx7I9DWg4cD0cyGjsvFrrBcACADc3t1bzeoVt01qT82kWNZnVhI6JwMHXwdoltTmOAY6E3BFO5ZEK8pbnkPNJFkXrCvAfFYhrgnu7nBVbCFtRmZl5StuFEFZSldV4q9Hxtp+i42UzrTWfffbZgZ49e/5t0o+NGzf+Y3imm5tbow13x8tt9VxdXfXll19e9OWXX3qfleDblJbZs+m+++7L8/LyMvXp06dy5cqVHvXbS0pK7MLDw2sA5s+f73+85w8ZMqRkzpw5ge+++24qQG5url3Duwcn8tlnn/l++eWX+4cNG1YOsG/fPsfhw4fHzp07N+OGG24oeOedd/x37tzp9umnnx4BuOSSS4rfeuutgMsvv7zUyclJ79ixwyk6OvofA96KiorsvLy8TB4eHuZt27Y5b9++3Q1g0KBB5VOnTo3Izc218/b2Ni1fvtynS5culQADBw4smTlzZuB///vfbKibIa1///6Vx567pVg6178D7NVaz2mw62vgdmCG5e/lDbZ/rJSaA4QCMcDvLVexECdW8msRpVuK8b3UH7cu7tYup01ziXYl/KEoyneWkrcyl4y303Dp7Ir/FYE4R7ic/ARCiFbHJSSkrptzI9uFEK2Ic3BNXTfnRrY3g+Nls6FDh5bMnj07aNGiRSkGg4FNmza5DBgwoNLT09NUVlbWpC50jeU2R0dHXVRUZBcVFVVbW1vL999/7zVgwIDSk52roTbTf69Tp061//nPf3KO3f74449nPfPMM+HnnXdevMl0/Bw7ffr0zKKiIruYmJiucXFxCd9++63HcQ9uIDEx0TEjI8PxoosuOtp3PT4+vsbd3d30448/ul199dUlf/zxh8fAgQNLnJ2dNcDEiRPz4uPjq7p3794lJiam65gxY6IadsGud8011xQbjUYVGxubMG3atNCePXuWA3To0KF24sSJmb179+4yYMCAuNjY2EovLy8TwIIFC1L//PNPt9jY2IROnTp1ff311xsdk9yCBgC3Ahcppf6y/PkXdYH3EqXUfuASy2O01ruBT4A9wPfA/VrrJt2AEOJsq0qpJPeLbFzj3fAdftz7aOIUKKVw7+FJ1OMdCRgdRE1mNalzjpD1UTq1Bc3yf68QogXFT56Mncvfb1zZubgQP3mylSoSQjSq+1PpGJz/3qJqcDbT/an05jj98bLZjBkzMoxGo4qPj0+IiYnp+uSTT4YBjBw5sjQpKcmlfnKrE527sdxWUlJiuOyyyzrHxsYmdOnSpau/v3/to48+mnsqNasTdavdvn37kZ49e+adyglF8yguLjZ4eXmZa2trufTSSzvfcccdebfddlvR2b7u9u3b/Xv27Bl9tq9zqtzc3HR5uawTKs4eU7mRlNmHAUXkI9HYubWZkSBtiqnSROGP+RStKwAN3oN88LnEv92vjyxEW5K2fDn7Zs2iMjMTl5AQ4idPlvG9wmYopSq01lZdNeV4Tjmb7Z/ny87nwqjKcsQ5uIbuT6Wf6fje1u5EWUY+2bVSjz76aOj69es9q6ur1eDBg0tuueWWImvXJISt0mZN1kcZmEpMhD8UJaH3LLJzscP/skC8+vuQ/10uhT8XUPxbMb7D/fEe4IOyl/G/QrR24VdeKUFXiLYgZlyBrQfdUyGf7lqpBQsWpFm7BiHai4LVeVTsKyfwumCcI2XsaUtw8HEg+KZQfAb7kvd1DnlfZVO8oQC/ywJxP8dDJsASQgghRLNqM2N8hRDibCjfW0bB6jw8envh2c/b2uW0O05hzoTdF0novREoRwNZH6ST9uoRKg9VWLs0IYQQQtiQk7X4ms1mszIYDLKUTDtgNpsVYNX1gIVoSbUFNWR9lIFjiBOB1wZLK6MVucW74xrrRskfxeR/l0vaa8m4dXfH//JAHAOdrF2eEEII0RpINjuBk2WZk7X47srNzfWynETYMLPZrHJzc72AXdauRYiWYK41k/leOpg1IXeEY3CUDjDWpgwKr77eRE/rhN+/AqhIqiB55iFyPsvCWGq0dnlCCCGEtUk2O46mZJkTtvgajcZ7srKy3s7KyuqGdIu2dWZgl9FovMfahQjREnK/zKY6rYqQu8JxDGiWtdxFMzE4GvC9xB/PC7wpWJVH8a+FlG4pxudiP7wH+8pNCiGEEO2SZLMTOmmWOeFyRkK0FrKckWhOJb8Xkb0kE5+L/fC/PNDa5YiTqMmpJm9lDuU7y7D3ssd3ZACevb1QBrnhLYQQonm15uWMxJmR4CvaBAm+orlUp1eR+uoRnKNcCBsXibKT8NRWVB6sIPfrbKpTqnAMdcJ/VCBu8e7WLksIIYQNkeBruyT4ijZBgq9oDqZKE6lzDmOu1UQ+0gF7D1nRra3RWlP2Vyn53+RQm1+La6wb/lcE4hTmbO3ShBBC2AAJvrZL+oYLIdoFbdZkf5xBbUEtIbeHSehto5RSeJzrSeSUjvhfFURVWiUpsw+T9XEGtUW11i5PCCGEjVNKvauUylFK/WMSJaXUZKWUVkr5N9g2VSl1QCmVqJS6tGWrFQ1Ji69oE6TFV5ypgrV55H+TS8DVQXhf6GvtckQzMVWYKFibR/H6QjCA92BffC72w87ZztqlCSGEaINO1uKrlLoQKAM+0Fp3a7A9AngbiAd6aa3zlFIJwBKgDxAKrAVitdams/kaROOkxVcIYfMq9peT/20u7ud64jXIx9rliGZk52pHwBVBRE3riHt3DwrX5pP8/EGKNhSgTXJjVwghRPPSWq8HChrZ9TLwGNDwP58rgaVa62qt9WHgAHUhWFiBBF8hGpG2fDlrBw1iRefOrB00iLTly61dkjhNxqJasj5IxzHQkaDrQ1BKJrOyRQ6+jgTfGkbExGgcQ5zI/SKb5JmHKNtRgvRsEkIIcTYppa4A0rXW24/ZFQakNnicZtkmrEAGuQlxjLTly9nxxBOYKisBqMzIYMcTTwAQfuWV1ixNnCJt1GS+n465VhN+ZzgGJ7nXZ+ucI10IGx9J+Z4y8lfkkPleOs4dXPC/IgiXaBdrlyeEEKL1s1dKbWnweIHWesHxDlZKuQJPAMMb293INrkbayUSfIU4xr5Zs46G3nqmykr2zZolwbeNyfs6m6ojlQTfFoZjkJO1yxEtRCmFe1cP3OLdKfmtiPzvc0l79QjuPT3wuywQxwBHa5cohBCi9TJqrc8/heM7AR2A7ZZeZeHAn0qpPtS18EY0ODYcyGiuQsWpkeArxDEqMzNPabtonUr/LKZoQyHeF/rica6ntcsRVqDsFF79ffDo5UXhT/kU/pRP2a5SvAf44DvcHzs3+S9QCCHEmdFa7wQC6x8rpY4A51smt/oa+FgpNYe6ya1igN+tUqiQMb5CHMslJOSUtovWpzqrmuxlmZYuroEnf4KwaQYnA34jAoie1gnP3t4UbSjkyPMHKfghH3Ot2drlCSGEaEOUUkuAX4E4pVSaUuru4x2rtd4NfALsAb4H7pcZna1HljMSbUJLLmd07BhfADsXF3q88IJ0dW4DzFUmUl4+grnCROTkDth7OVi7JNHKVGdWk7cyh4o9Zdj72OP3r0A8zvNEGWTiMyGEaO9OtpyRaLsk+Io2oaXX8U1bvpx9s2ZRmZmJS0gI8ZMnS+htA7TWZL2fTtmOUsLGR+LaWf7fEsdXsb+cvK9zqE6rwincGf8rAnGNkX8zQgjRnknwtV0SfEWb0NLBV7RNhesKyPsqG7/LA/G92M/a5Yg2QJs1pdtKyP8mB2OhEdcubviPCsIpRCZDE0KI9kiCr+2S4CvaBAm+4mQqD1WQ9kYybl3dCbkzXNbrFafEXGumeEMhBWvyMFeb8ezrjd8If+kqL4QQ7YwEX9slwVe0CRJ8xYkYS4ykzD6MwVERMakDdi521i5JtFGmciMFq/Mp2lSAslP4DPHD5yI/WQNaCCHaCQm+tkuCr0Ap5QZUteZZ5iT4iuPRJk36WylUpVQSMSEap1Bna5ckbEBNXg353+RQ9lcpdh52+I0IwLOvN8pOehIIIYQtk+Bru+QWdjuklDIopW5SSn2jlMoB9gGZSqndSqmXlFIx1q5RiKbK/zaXyoMVBF4XIqFXNBtHf0dCbg8nYkI0Dv6O5HyaRcpLhyjbVYrcMBbtWW55Lk/99BQJbyQw7YdplFaXWrskIYRoEmnxbYeUUuuAtcByYJfW2mzZ7gsMBW4CvtRaf2S9Kv9OWnxFY8p2lJD5Xjpe/b0JvE7WWRZnh9aa8l1l5K3IoTa3BpdOrvhfEYhzpIu1SxOixaQUpzDrl1m8/efbVBor6R3amz8y/iDYPZjpF0/ntp63YVDSniLaPmnxtV0SfNshpZSD1rr2TI9pSRJ8xbFqcmtInXMYh0BHwh+MwmAvH7jE2aVNmuJfCylYlYepzIT7eZ74XxaAg6+jtUsT4qzZnbObF395kY93fgzALT1u4bH+j9EloAu/p//OhO8n8Gvar/QK6cUrI15hYORAK1csxJmR4Gu7JPiKNkGCr2jIXG0m9dUjGEuMRD7SAQcfmXlXtBxTlYnCH/IpWlcAZvAa5IPvJf7YucqkasJ2bE7bzIyNM1ieuBxXB1fGnjeWSf0mEeEV8bfjtNYs2bWEx9c+TlpJGv/u+m9mDptJtHe0dQoX4gxJ8LVdEnzbGaXUOKAX8ANwC/CN1vot61Z1chJ8RT2tNdmLMyj9s4TQsRG4xbtbuyTRTtUW1ZL/XS6lfxRjcDHge4k/XgN9pPeBaLO01qw+uJrpG6ezLnkdvi6+PNjnQR7o8wD+rv4nfG5FbQUvbXqJmZtmYtZmJvefzJSBU3B3lN/Rom2R4Gu7JPi2M0qpT4DrgQ1a64FKqXla63FneM53gcuBHK11N8u2ZUCc5RBvoEhrfY5SKhrYCyRa9m1uyvUl+Ip6RZsKyf0sC98R/vhdGmDtcoSgOr2KvBU5VCSWY+/rgP/lgbif4yFrSYs2w2Q28dmez5ixaQZ/Zf1FmEcYj/R7hDG9xpxycE0rSWPK2iks3rmYEPcQpl88nVt73irjf0WbIcHXdknwbWeUUm9pre9TSo3SWq9QSr2qtX74DM95IVAGfFAffI/ZPxso1lo/Zwm+Kxs77kQk+AqAquRK0l5LxiXWldB7IlAGCRai9SjfVzcBVk1GNU6RzgRcEYRLJ1drlyXEcVUZq/hg+we8uOlFDhYeJM4vjscHPM7NPW7G0e7Mxq5vTtvMhO8n8Fv6b5wfej6vXPoKAyIHNFPlQpw9EnxtlwTfdkYpFa+13tfg8WCt9bpmOG80jQRaVdfkkQJcpLXeL8FXnC5TmZGU2YdBKSIf6YCdm4ynFK2PNmtKtxST/20uxmIjbt3c8b88EMcgJ2uXJsRRJdUlzNsyj5c3v0xWWRbnh57P1IFTuTLuSuwMzfe71azNLNlZN/43vTSd67tez8xhM4nyjmq2awjR3CT42i4Jvu2YUuo64HutdalS6kngPOB5rfWfp3GuaBoPvhcCc7TW5zc4bjeQBJQAT2qtN5zs/BJ82zdt1mQsSKXyQAXhD0fhHCHLyIjWzVxjpmhdAYU/5GOuNePVzxvfSwOw97C3dmmiHcspz+HVza/yxh9vUFxdzLCOw5gyYAoXdbjorHbNL68p56VfXuLFTS+i0UzuN5nHBz4u439FqyTB13ZJ8G3HlFI7tNY9lFIDgenALGCa1rrvaZwrmsaD71vAAa31bMtjJ8Bda52vlOoFfAV01VqXNHLOscBYAEdHx17V1dWnWpawEfnf5VKwOo/Afwfj1c/H2uUI0WTGUiMFq/Mo/qUQ5WDA9yI/vIf4YnCU8Y6i5RwpOsKsX2bxzrZ3qDZWM7rLaKYMnML5oee3aB2pxalM+WEKH+/8mFCPUKZfPJ1betwi439FqyLB13ZJ8G3HlFLbtNbnKqWmAzu11h/XbzuNc0VzTPBVStkD6UAvrXXacZ73MzBZa73lROeXFt/2q3xPGRkLU/Hs40XgDSEyYZBok2pyqslbmUv5zlLsvOzxGxmAZ28vGacuzqqd2TuZuWkmS3ctxaAM3NbzNh7t/yhx/nEnf/JZ9Gvqr0xYNYHf03+nd2hvXhnxCv0j+lu1JiHqSfC1XRJ82zGl1Erqgukw6pY4qgR+11r3PI1zRfPP4DsCmKq1HtxgWwBQoLU2KaU6AhuA7lrrghOdX4Jv+1SbX0PKnMPYezsQ8XC0tJKJNq/yUAV5X+dQlVyJY4gT/qMCcY13kxs6olltStnEjE0zWJm0EjcHN+7tdS+T+k0izDPM2qUdZdZmPt75MVPWTiG9NJ0but3AzGEzifSKtHZpop2T4Gu7JPi2Y0opV2AEda29+5VSIdSF0NWneJ4lwBDAH8gGntZav6OUWkTdckXzGhx7DfAcYARMlmNXnOwaEnzbH3OtmbS5ydTm1RDxSAcc/c9shlEhWgutNWXbS8lfmUNtfi0usW4EXBGIU5iztUsTbZjWmu8OfMeMjTPYkLIBPxc/Hur7EA/0eQBfF19rl3dc5TXlvLjpRV785UUAHu3/KI8PeBw3R8kdwjok+NouCb7tkFKqH3WBtM188yX4tj/ZyzIp2VxEyN3huHfzsHY5QjQ7bdQUbSqkYHUe5koTHr288PtXAA4+DtYuTbQhRrORT3d/yoxNM9iRvYMIzwgm95/M3efe3abCY0pxClPWTmHJriWEeoQy4+IZ3NzjZhn/K1qcBF/bJcG3HVJKzQP6UDez8vfUzeycZd2qTkyCb/tS/FsROUsz8Rnmh/9lgdYuR4izylRponBtPkXrC0CB94W++Fzsh52LLNkljq/KWMV7297jpV9e4nDRYbr4d+HxAY9zU/ebcLBruzdPfkn9hQnfT+CPjD/oE9aHVy59hX4R/axdlmhHJPjaLgm+7ZhSKh4YCVwKeAE/UReEN2mtTdas7VgSfNuPqrQq0uYewTnahbBxkTL5j2g3agtqyf82h9KtJdi52eE73B+v/j4oe/kZEP+vuKqYt7a8xSubXyG7PJu+YX2ZOnAqo+JG2UzrqFmbWbxjMVN+mEJGaQY3druRmcNmEuEVYe3SRDsgwdd2SfAVACilXICh1AXhfvXr7rYWEnzbB1OFidQ5h9FGTcQjHWTNU9EuVaVWkrcih8r9FTj4O+B3eSDuPTxkAqx2Lqssi1c3v8qbW96kpLqESztdypSBUxgcNdhm/22U1ZTx4qYXeemXl1AoHu3/KI8NeKxNdeEWbY8EX9slwbedUUqNo24G5x+AW4BvtNZvWbeqk5Pga/u0WZP5bhrl+8oIfyAKl2hXa5ckhNVoranYW07eihxqsqpxjnbB/4pAXDrIz0V7c6jwEC9teon3/nqPGlMN13W9jscHPM55IedZu7QWk1yUzJQfprB011LCPMKYMWwGN3W/yWZauEXrIsHXdknwbWeUUp8A1wMbtNYDlVLztNbjrF3XyUjwtX0Fa/LI/zaXgNFBeA9qvTOQCtGStElT8kcR+d/mYio14d7DA7/LA3EMkFnObd32rO3M3DSTZbuXYW+w5/aet/No/0eJ8YuxdmlWsyllExNWTWBLxhb6hvXllRGvcEH4BdYuS9gYCb62S4JvO6OUektrfZ9SapTWeoVS6lWt9cPWrutkJPjatorEctLnp+B+rifBt4TabLc9IU6XudpM4U/5FP6UjzZqvAb44DfcHzt3GQ5gS7TWbEzZyIxNM/h2/7e4O7pz3/n3MeGCCYR6hFq7vFbBrM18uP1Dpv4wlcyyTG7qfhMzLp4h439Fs5Hga7sk+LYzSql4rfW+Bo8Ha63XWbOmppDga7tqi2pJnXUYO3c7IiZ2wOAkXdeEOB5jiZH873Mp2VyEwcmAz8V+eF/oi8FRfm7aMrM28+3+b5m+cTq/pP5CgGsAD/d9mPG9x+Pj4mPt8lqlspoyZmycwaxfZmFQBh4f8DiPDngUVwcZDiDOjARf2yXBV7QJEnxtkzZq0l5PpjqrmsiJ0TgGOVm7JCHahOqsavJX5FC+pwx7b3v8/hWARy8vmQW9jak11bJs9zJmbprJrpxdRHlFMbn/ZO469y4JcE2UXJTM42sfZ9nuZYR7hjNz2Exu7Haj9BwSp02Cr+2S4NuOKaXOB54AogB7QAFaa93DqoU1QoKvbcr5PIvijYUE3x6Gxzme1i5HiDan4kA5ectzqE6rwinMCf9RQbjGyee11q6itoL3tr3HrF9ncaToCF0DujJl4BSu73p9m16D15o2pmxkwvcT2Jq5lQvCL+CVS1+hb3hfa5cl2iAJvrZLgm87ppRKBB4FdgLm+u1a62SrFXUcEnxtT8nWYrI/ysB7iC8BVwZZuxwh2ixt1pRuKyH/m1yMhbW4xrvhPyoQp1Bna5cmjlFYWcibf7zJq7+9Sm5FLv3C+zF14FQui71MZihuBmZt5oPtHzD1h6lklWVxS49bmH7xdMI9w61dmmhDJPjaLgm+7ZhSaqPWeqC162gKCb62pTqzmtRXDuMU5kz4/VEoO+mSJsSZMteaKd5YSMGaPMxVZjz7ehNwdZCM/20FMkszeXnzy8zbMo/SmlJGdh7J1IFTGRg5ULrkngVlNWVM3zCd2b/Oxs5gx+MDHmdy/8nSfVw0iQRf2yXBtx1TSl0M3Ejdmr7V9du11l9YrajjkOBrO0xVJlLnHMFcZSLykQ7Ye0m3PiGak6ncSMGafIrWF+DSyZXQeyJk0jgrOVBwgJc2vcSi7Yswmo1c3/V6Hh/wOD2De1q7tHbhSNERHl/7OJ/s/oQIzwhmDpvJDd1ukJsN4oQk+NouCb7tmFLqIyAe2M3/d3XWWuu7rFdV4yT42gatNVmL0inbVUrYfZG4dpb/V4Q4W0q2FpP9cQbOUS6Ejo3AztnO2iW1G9sytzFj0ww+2/MZDgYH7jznTib3n0wn307WLq1d2pC8gQmrJvBn5p/0C+/HKyNeoU9YH2uXJVopCb62S4JvO6aU2qm17m7tOppCgq9tKPw5n7zlOfhfEYjPUD9rlyOEzSvdXkLWB+k4hTsTdm8kdq4Sfs8WrTXrktcxY+MMVh1chYejB+N7j2fCBRMIdg+2dnntnlmbef+v95n24zSyyrK4tcetTL94OmGeYdYuTbQyEnxtlwTfdkwptRB4WWu9x9q1nIwE37av8mAFaW8m49bNg5A7wqSrmRAtpGxXKVmL0nEMdiRsXCR27vbWLsmmmLWZFYkrmLFpBpvTNhPoFsjECyYy7vxxeDt7W7s8cYzS6lKmb5zOnF/nYGewY8qAKUzuPxkXBxdrlyYayKmpwdPODme7lr9ZJ8HXdknwbceUUnuBTsBh6sb4ynJG4qwwlhhJmXUIg7MdEROjsXORVichWlL53jIy30vDwd+RsPsisfeQ8Humak21fLzzY2ZumsnevL108O7Ao/0f5Y5z7pAQ1QYcLjzMY2sf47M9nxHhGcGLl7zI9V2vl5uyVqa1ZnF2Ng8fOMD4sDD+26FDi9cgwdd2SfBtx5RSUY1tl+WMRHPSJk36WylUpVQSMSFallgRwkoqksrJeCcVe28HwsdHysRyp6mitoK3/3ybWb/MIrUkle6B3ZkycAr/7vpv7A1yQ6GtWZ+8ngnfT2Bb1jb6R/TnlUtfoXdYb2uX1S6lVlUxLimJbwsK6OfpyTtxcXRxa/n8KcHXdknwbYeUUkqf5BvflGNakgTftiv362yKfiog6JZQPHt5WbscIdq1yoMVpC9Mxd7DjrDxUTj4SPhtqoLKAt74/Q3m/j6XvIo8BkYOZOrAqYzsPFJaCds4k9nE+9vfZ9oP08guz+a2nrcx/eLphHqEWru0dsGsNQszM3n04EFMWvO/jh15ICwMOyv9XEnwtV0SfNshpdTPwOfAcq11SoPtjsBA4HbgJ631IqsU2AgJvm1T2Y4SMt9Lx2uAD4HXyuQuQrQGlUcqyZifgsHVjvDxkTj4OVq7pFYtvSSdOb/OYf7W+ZTXlnN57OU8PuBxBkYOtHZpopmVVJcwfcN05myeg73BnqkDp/JIv0ek6/pZdLCyknsSE/m5qIiLvb1ZEBdHRxfrvt8SfG2XBN92SCnlDNwF3Ax0AIoAZ8AOWA28obX+y1r1NUaCb9tTk1NN6pwjOAQ5Ev5gFAZ7WUdUiNaiKrWS9HkpGBwNhI2PwjFAwu+xkvKTeHHTi3yw/QPM2swN3W7g8QGP0z2oTSyGIM7AocJDPLbmMT7f+zmRXpG8OOxF/t3139Ky34xMWvNqWhpPHj6Mg1LM7tSJu0NCWsV7LMHXdknwbeeUUg6AP1CptS6ycjnHJcG3bTFXm0l99QjGEiORj3SQ7pRCtELV6VWkv5UCdorw8ZE4BjlZu6RWYWvGVmZsmsHnez7Hyd6Ju865i8n9J9PBp+Un2RHW9fORn5m4aiJ/Zf3FgIgBvDLiFc4PPd/aZbV5u8vLuXvfPn4rLWWUnx9vxcYS5tR6fv9I8LVdEnxFmyDBt+3QWpO9OIPSP0sIvTcCtzh3a5ckhDiO6qxq0t9MBg1h90W228nntNb8dOQnpm+cztpDa/Fy8uL+3vfzUN+HCHIPsnZ5wopMZhOL/lrEtB+nkVOewx3n3MELF70g439PQ63ZzIyUFP6bnIyXvT1zO3fmhsDAVtHK25AEX9slwVe0CRJ8246ijQXkfp6N38gAfIf7W7scIcRJ1ORUk/5mCuZaTdi4CJwj2s94RrM289W+r5ixcQZ/ZPxBsHvw0TV4PZ08rV2eaEVKqkv434b/8fLml3EwODB14FQm9Zsk43+baGtpKXft28eO8nJuCAxkbufOBDi2ziEWEnxtlwRf0SZI8G0bqpIrSX3tCK6xboTeE4EytK67uEKIxtXm1ZD2ZgrmKhNh90biHGXbH+ZrTDUs3rGYmZtmkpifSCefTjw24DFu63kbzvbts9VbNM3BgoM8tvYxvtj7BVFeUbx4yYtcl3Bdq2u1bC0qTSaePXKEWampBDo6Mi82liv8W/dNcQm+tkuCr2gTJPi2fsYyI6mzD4NBETmpA3ZudtYuSQhxCmoLakl/KxlTqYnQsRG4dHS1dknNrqymjLf/fJvZv84mrSSNc4LPYcqAKVyTcI2swStOyU+Hf2Liqolsz97OwMiBvHLpK/QK7WXtslqVjUVF3J2YSFJlJXcHBzOrUye8HVr/nB8SfG2XBN92SCk16UT7tdZzWqqWppLg27ppsyZ9fipVhyoIfyiqXXWVFMKWGItqSXsrBWNRLaH3ROAaYxuf/fIr8nnt99d47ffXKKgsYHDUYKYMnMKlnS6Vljpx2kxmE+9ue5cnfnyCvIq8o+N/QzxCrF2aVZUZjUw9fJg30tOJcnZmYWwsw3x9rV1Wk0nwtV0SfNshpdTTli/jgN7A15bHo4D1Wut7rFLYCUjwbd3yv82hYE0+gdeH4HWBt7XLEUKcAWOJkfS3UqjNryHkrnDc4tvuBHWpxanM+XUOC/5cQEVtBVfEXcGUAVPoF9HP2qUJG1JcVcwLG17glc2v4GjnyLRB05jUb1K77Da/pqCAMYmJpFRX82BYGC906IC7fdvqTSHB13ZJ8G3HlFKrgWu01qWWxx7Ap1rrEdat7J8k+LZe5btLyXg7Dc++XgTdILNcCmELjGWW8JtdQ/CdYbh39bB2SadkX94+Xtz0Ih/t+AizNnNzj5t5rP9jdA3sau3ShA07UHCAR9c8ylf7viLaO5oXh73ItQnXtoteBYW1tTxy8CDvZWUR5+LCO/HxDPDysnZZp0WCr+0yWLsAYVWRQE2DxzVA9KmeRCn1rlIqRym1q8G2Z5RS6Uqpvyx//tVg31Sl1AGlVKJS6tIzeQHCumrza8hanIFTmBMBo4OtXY4QopnYu9sTPj4Kx1AnMt9Lo2xHibVLapLf039n9LLRJLyRwNJdSxl3/jgOPnSQ9696X0KvOOs6+3bmy+u/5IfbfsDTyZN/f/ZvBi8azJ+Zf1q7tLPqq9xcEv74gw+yspgaGclf55/fZkOvsG3S4tuOKaWeAP4NfAlo4GrgE631/07xPBcCZcAHWutulm3PAGVa61nHHJsALAH6AKHAWiBWa2060TWkxbf1MdeYSZt7hNqCWiIndcDBv3UuSyCEOH2mShMZC1KpSqkk+OZQPM5rfR9mtdasPbSWGZtm8OPhH/F29uaB3g/wUN+HCHALsHZ5op0ymU28s+0dnvzxSfIq8rjznDt54eIXCHa3nZvEOTU1PLh/P5/k5tLTzY134+M5z6Nt9Q5pzMlafJVS7wKXAzkNPve+RN2QwRrgIHCn1rrIsm8qcDdgAh7SWq86u69AHI8E33ZOKXUeMMjycL3WettpnicaWNmE4DsVQGs93fJ4FfCM1vrXE51fgm/rk700g5Lfigm5J7zNdYMUQjSducpExttpVB6qIOjGEDx7e1u7JKAuWHy570tmbJzB1sythHqEMumCSYztNRYPJ/mdJFqH4qpinl//PK/+9ipO9k5MGziNif0mtunxv1prPs7J4eH9+yk1mXgqOprHIiJwMNhGR9ImBN/GGnyGAz9qrY1KqZkAWuvHT7XBRyn1ALBYa13YrC9KANLVuV1TdYNOEgAvrfWrQL5Sqk8zXuIBpdQOS1doH8u2MCC1wTFplm2iDSneXETJb8X4XOInoVcIG2dwtqtb3ijGjewlmRRvtu7nsWpjNW//+TZd3ujCdZ9eR0l1CQtHLeTQQ4d4pP8jEnpFq+Ll7MVLw19iz/17uLjDxUz7cRoJbyTw+Z7PaYuNT2lVVYzauZNb9u4lxtWVbeefzxNRUTYTeptCa70eKDhm22qttdHycDMQbvn6SmCp1rpaa30YOEBdCD6eYOAPpdQnSqkRqj0MEG9B7edfqWjMm0A/4EbL41LgjWY691tAJ+AcIBOYbdne2A9wo7/5lVJjlVJblFJbjEZjY4cIK6hKqyL38yxcYt3wGyHdCIVoDwyOBkLvCcc13o2cZVkUbSw4+ZOaWWl1KbN/mU3HuR0Zs2IMHk4efHrdp+y9fy/3nHcPTvZOLV6TEE3V2bczX93wFWtvXYu7ozvXfnotQ94fwrbM0+po1+K01izIyKDrH3/wY1ERL3fqxMZzzyXBzSbngLKv//xp+TP2FJ9/F/Cd5etTavDRWj8JxADvAHcA+5VS/1NKdTrFGkQj2tb84qK59dVan6eU2gagtS5USjXLQE2tdXb910qphcBKy8M0IKLBoeFAxnHOsQBYAHVdnZujLnFmTBUmMt9Lw87djuBbQ1EGuREpRHthcDAQclc4We+nk/t5Ntqo8Rnid9avm1uey2u/v8brv79OYVUhF3W4iEVXLmJYx2HtYrZcYVsu7ngxf977J+/8+Q5P/vQkvRb04q5z7+KFi14gyD3I2uU16mBlJWMSE/mpqIiLvL1ZGBdHRxcXa5d1Nhm11uefzhMt8+cYgcX1mxo57ISfabXWWimVBWRZzuUDfKaUWqO1fux06hJ1pMW3fatVStlh+QFUSgUA5uY4sVKq4ertVwP1Mz5/DdyglHJSSnWg7q7W781xTXF2abMma3EGxuJagm8Px95d7psJ0d4Y7A2E3BGOe08P8pbnULAm76xdK7komYe+e4ioV6L47/r/MiR6CJvv3swPt/3AJZ0ukdAr2ix7gz33nn8v+x/cz6R+k/hg+wfEvBbDzI0zqTJWWbu8o0xa83JqKt3/+IOtpaUsiI1lbc+eth56T5tS6nbqJr26Wf9/P/YmN/hYzvGQUmor8CKwCeiutb4P6AVcc1YKb0dkcqt2TCl1M3A9dT9Mi4BrgSe11p+e4nmWAEMAfyAbeNry+BzqQvUR4F6tdabl+Ceo6wZiBCZorb879pzHksmtrK9gTR753+YScE0Q3gN9rV2OEMKKtEmTvSSD0q0l+A73x3eEf7MF0d05u3nxlxf5eOfHANzS4xYe6/8YXQK6NMv5hWht9ufvZ/KayXyd+DUdvDswa/gsro6/2qo3d/aUl3N3YiKbS0q43M+Pt2JiCHduuxNynYqmrOPbyKSuI4A5wGCtdW6D47oCH/P/k1v9AMScYHKr54B3tNbJjezrorXee3qvSoAE33ZPKRUPXGx5+GNr/YGS4Gtd5YllZMxPxeNcT4JuCZWWFiEE2qzJ+SSzbqK7i/zwuzzgjH43bE7bzIyNM1ieuBxXB1fGnjeWSf0mEeEVcfInC2ED1h5ay8RVE9mVs4sh0UN4+dKXOSf4nBatodZsZmZKCv9NTsbDzo65MTHcGBjYrv7fb8Kszo01+EwFnIB8y2GbtdbjLMefcoOPUioQOHqnQWudclovRvyNBN92TCnlDIynbjkjM7AReEtr3Xr62VhI8LWe2sJaUmcfxs7DnogJ0RicZISEEKKONmtyv8iieFMR3hf64n/VqX1A1lqz6uAqZmycwbrkdfi6+PJgnwd5oM8D+Lv6n8XKhWidjGYjC7cu5D8//YeCygLuPvdunr/o+RYZ//tnaSl37dvH9vJyrg8IYG5MDIGOzTL1S5vSlBbfs3jtUdS1HIcCOUAUsFdr3dUa9dgaCb7tmFLqE+pmcv7IsulGwEdrfZ31qmqcBF/rMBvNpL2WTG12DRGTonEMlFlThRB/p7Um76tsitYX4jXAm4DRwSed+M5kNvHZns+YsWkGf2X9RZhHGI/0e4Qxvcbg7ujeQpUL0XoVVRXx33X/Ze7vc3Gxd+HJC5/k4b4Pn5XZy6tMJp5NTuallBQCHR15MyaGqwLa76oNVg6+24GLgLVa63OVUkOBG7XWpzqztGiEBN92TCm1XWvd82TbWgMJvtaR83kWxRsLCb4jDI+entYuRwjRSmmtyV+ZS+GP+Xj29SLw3yGNht8qYxUfbP+AFze9yMHCg8T5xfH4gMe5ucfNONq1v5YlIU4mKT+JyasnsyJpBR19OjLrkllcFX9Vs3U93lRczN379pFYWcldwcHM6tQJHweHZjl3W2Xl4LtFa32+JQCfq7U2K6V+11qfaO1f0UQyLWv7tk0pdYHWejOAUqovdTPICUHJ1mKKNxbiPcRXQq8Q4oSUUnVjfO0VBavz0EZN0I2hKLu6D+cl1SXM2zKPlze/TFZZFueHns/nl3zOlXFXYmews3L1QrResX6xfH3j16w+uJpJqyYx+pPRDI0eysuXvkzP4NNvpygzGpl2+DCvp6cT6eTE6h49uMRXJq5sBYqUUu7ABmCxUiqHurHBohlIi287pJTaSd1syw5AHFA/YD4S2FM/Q11rIi2+Las6s4rUV47gHOFC2H2RRz+8CiHEydTPAO/e0wPDaAfm/jGXN/54g+LqYoZ1HMaUAVO4qMNF7WqyHCGag9FsZMHWBTz101MUVBZwz3n38PxFzxPoFnhK51lbUMCYpCSSq6p4ICyM/3XogLu9tIXVs3KLrxtQSd2SszcDXsBirXX+CZ8omkSCbzuklIo60f7GplC3Ngm+LcdUZSJ1zhHMVSYiH+mAvVf77vIkhDh1B7/dj3mNkR8df+Ihl4mMShjFlIFTOD/0fGuXJkSbV1hZyHPrnuP1P17H1cGVJwc9yUN9Hzrp+N+i2loeOXiQd7OyiHVx4Z24OAZ6e7dM0W2IlYOvNxBjeZiktS62Rh22SoJvO6aUeqqx7Vrr51q6lpOR4NsytNZkLkqnfFcp4eOjcOnkau2ShBBtyM7snczcNJOlu5Zyc/WNPFkxDd0JOt8bh8FBZoQXojkl5iXyyOpH+Gb/N3Ty6cSs4bO4Mu7KRntTLM/L476kJHJqang0MpKnoqJwsZNhBo2xRvBVSjkCC4CrgMOAom5G5y+BcVrrmpasx1bJ/0LtW3mDPyZgJBBtzYKEdRX9XED5jlL8Lw+U0CuEaLJNKZsYtWQUPeb14Kt9X/Fw34f53+MzCPx3MOoQZLydhrnGbO0yhbApcf5xrLxpJd/f/D1O9k5cvexqhn04jB3ZO44ek1tTww27d3PVrl0EODjwW69eTO/YUUJv6/MkdUMQI7TW52qtz6FuCKI98B9rFmZLpMVXHKWUcgK+1lpfau1ajiUtvmdf5cEK0t5Mxr2bB8F3hMn4OyHECWmt+e7Ad0zfOJ2NKRvxc/Hjob4P8UCfB/B1+f9Jckp+LyJ7aSYuHV0JvSccg7N84BaiuRnNRuZvmc9TPz9FUVURd597D+f2nMx/UrIpNZn4T1QUj0VG4miQNq+TsVKL7y6gj9a64pjt7sDm1jj/TlskwVccpZTyAX7XWsec9OAWJsH37DIW15Iy+zAGZzsiJkVjJx9MhWiz0pYvZ9+sWVRmZuISEkL85MmEX3lls53faDby6e5PmbFpBjuydxDhGcHk/pO5+9y7cXNs/LNi6Z/FZC3OwDnShdCxEdi5yO8YIc6GwspCHl03k3fLvdB+/YhUZXx97kB6enpbu7Q2w0rBd4fWusdx9u3UWndvyXpslUzh1o41mN0ZwA4IAFrd+F5xdmmTJvP9dMzVZsLui5TQK0QblrZ8OTueeAJTZSUAlRkZ7HjiCYAzDr+VtZUs+msRL/3yEoeLDtPFvwuLrlzETd1vwsHuxJPgeZznhbJXZH6QTvpbKYTdG4mdm/yuEaI5aa35rLCST90uw8nFRHTRT+z763mu3VG3/u8VcVdIb67WS1saoBr7Bsk4kWYiLb7t2DGzOxuBbK11q1wrTFp8z57c5dkU/VxA0C2hePbysnY5QogzsHbQICozMv6x3SU0lGEbNpzWOYurinlry1u8svkVssuz6RvWl6kDpzIqbhQGdWrdJst2l5L1XjqOwY6EjYvEzl3uvwvRHA5VVjImMZEfi4oY4u3NwthYOru68v2B75m0ahJ78/ZycYeLefnSl+keJI2HJ2KlFt8j1AXcxoKv1lp3bMl6bJUE33ZIKdUZCNJabzpm+yAgQ2t90DqVHZ8E37Oj9K8Sst5Px2ugD4HXBFu7HCHEGVrRuTM09v+6Uow6cOCUzpVVlsWrm1/lzS1vUlJdwqWdLmXKwCkMjhp8Rq1G5fvKyHw3DQc/R8LGR2LvIeFXiNNl0prX0tJ44vBh7JRiVqdO3BMSgqHBz2itqZb5W+fz9M9PU1RVxNjzxvLc0OcIcAuwYuWtlzWXMxJnl4xwb59eAUob2V5p2SfagZqcarKXZuIc5UzAlUHWLkcI0QxcQkJOaXtjDhYc5L6V9xH9SjQzN81kROcRbB27le9v+Z4h0UPOuKukW7w7oWMiqC2oIe31ZIxFtWd0PiHaq73l5Qzato2JBw8yxNub3b17MzY09G+hF8DBzoEH+jzA/gf380DvB1j450JiXothzq9zqDHJKjmi/ZAW33ZIKbXreLPDtdYB9NLi27zM1WZSXz6MqcxExCMdcPA58fg8IUTbcOwYXwA7Fxd6vPDCScf4bs/azsxNM1m2exn2Bntu73k7j/Z/lBi/szPfYeWhCjIWpGLnYUfY+Cj5PSREE9WazbyYmspzR47gbmfH3JgYbgoMbPJNqb25e3lk9SN8d+A7Ovt2Zvbw2YyKHSXjfy2kxdd2SfBth5RSB7TWnU91nzVJ8G0+WmuyPsqgbFsJYfdG4honv9uFsCWnMquz1pqNKRuZsWkG3+7/FndHd+47/z4mXDCBUI/Qs15rVXIl6fNSMLjYET4+Egd/x7N+TSHasm2lpdyVmMhfZWVcFxDAazExBDme3s/Nd/u/Y9LqSezL28ewjsOYM3yOjP9Fgq8tk+DbDimllgA/aq0XHrP9bmC41vp661R2fBJ8m0/RhgJyv8jG718B+F7ib+1yhBBWYNZmvkn6hhmbZvBL6i/4u/ozoe8Exvcej4+LT4vWUpVaSfq8VAwOirDxkTgGOrXo9YVoC6pMJv6bnMzMlBQCHB15MyaGqwPOfIxuramWeVvm8fTPT1NcXcy9ve7l2SHPtuvxv9YKvkopA7BD1uw9eyT4tkNKqSDgS6AG2GrZfD7gCFyttc6yVm3HI8G3eVQeqSDt9WTc4twJuTscZZBuTULYmkqTifeysvihsJDL/Py4PjAQN7u6pYNqTbUs272MmZtmsitnF1FeUUzuP5m7zr0LVwdXq9VcnVFF+lspoCBsfBROwRJ+haj3S3Exdycmsq+igjuCg5nTqRM+Ds07NCC/Ip9n1z3Lm3+8ibujO08Pfpr7+9yPo13764VhzRZfpdRiYKrWOsUa17d1EnzbMaXUUKD+rtJurfWP1qznRCT4njljmZHUWYfBThH5SAfsXGUNTSFsSYnRyFsZGbycmkp2bS3+Dg7k1dbiYWfHv/198SvezCe/Pc+RoiN0DejKlIFTuL7r9Sddg7el1GRXk/ZmCpg0YfdF4hTmbO2ShLCqcpOJaYcO8Vp6OhFOTiyIi+NSX9+zes09uXuYtGoSqw6uItYvltnDZ3NZzGXtavyvlYPvj0Bv4Hfg6AdfrfUV1qjH1kjwFW2CBN8zo82a9HkpVB2uJPzhaJzD5QOlELYip6aGV9PSeCM9nWKTiUt9fJgaFcWFXl58n5vGtD2/8pfJC+yccKtO59YAP/7X/SJ8HFpfS05Nbg3pbyZjrjETNi4S5wgXa5ckhFWsLShgTFISR6qquD80lOkdO+Jh33JLf327/1smrZpEYn4il3S8hJcvfZmugV1b7PrWZOXgO7ix7VrrdS1diy2S4CvaBAm+ZybvmxwK1+YTeEMIXn29rV2OEKIZpFRVMSs1lbczM6kymxnh5cKNXhBoLiK/Mp8/M/9kwdYFlNaUMizmKrp3n8BP1W78VVaGq8HAvwMDGRMSQj9Pz1bVmlObX0PamymYK0yE3huJS7SEX9F+FNXWMvngQd7JyiLGxYV34uIY5O1tlVpqTbW8+cebPLPuGUqqSxjXaxzPDn0Wf1fbnh9EJreyXRJ8RZsgwff0le0qJfOdNDwv8Cbo+qav5SmEaFlaaypqKyioLCC/Mr/u74r8f3ydXAu7nXuQ694TtEblrEWnfAyVqX87n0EZuL7r9Tw+4HF6Bvc8eo2tpaUszMzk45wcykwmElxdGRMSwq3Bwfg187jB01VbWEv6m8kYS02EjYnApZP1xh8L0VJW5OUxLimJrJoaJkdE8Ex0NC521h+WlF+Rz9M/P828LfPwcPLg6cFPM773eJsd/2vlFt8LgNeALtTNvWMHlGutPa1Rj62R4CvaBAm+p6c2r4aU2Ydx8Hck/KEoDA4Ga5ckRLtQY6ohvyL/pCH22P3VpurjntPJuweGqFuo9OqFQZvoWLWHvjqZSGdn/Fz88HP1w9fFFz+Xur+D3YNPOENzmdHIstxcFmZk8FtpKY5KcU1AAGNCQhji7W31VmBjcS1pb6ZgLKol9J4IXGOkAUbYptyaGh4+cIAlOTl0d3Pj3bg4zvdsfTlnd85uJq2exOqDq4n1i2XO8Dn8K+ZfVv9d0dysHHy3ADcAn1I38extQIzWepo16rE1EnzbIaXUpBPt11rPaalamkqC76kz15hJm3uE2oJaIh/pgIOfbd6ZFeJsMplNFFYV/i3E/iPQNrKtrKbsuOd0MDjg5+p3NKD6ufrh6+z7z20uvvg6+5JodmV+Tik/FBXjbW/PA2FhPBQWRsBprt3ZmJ1lZSzMzOTD7GyKjEY6u7hwT0gItwcFEexkvRmWjaVG0t9KoTavhpC7wnGLd7daLUI0N601y3JyePDAAYqNRp6MimJKZCSOhtZ7k1prXTf+d/UkkvKTGN5pOHOGz7Gp8b/WDr5a6/OVUju01j0s237RWve3Rj22RoJvO6SUetryZRx1M8d9bXk8Clivtb7HKoWdgATfU6O1JmdpJiW/FxN6TzhuXT2sXZIQVqW1pqS65B8h9WQhtqiq6LjnNCgDPs4+/wisR79ubJurH24ObidtITFrzYr8fKYnJ/NbaSlBDg48EhHBvaGheJ5kgpvFi+GJJyAlBSIj4YUX4Oabm/Y+VZpMfJ6by8LMTNYXF2OvFKP8/BgTEsJwX1/srNCyYyozkj4vhZqsGoLvCMO9m/w+E21fenU145OS+Do/nz4eHrwTF0c397ZzY6fGVMObf7zJs+uepbS6lHHnj+PZIc/i5+pn7dLOmJWD73pgGPA2kAVkAndorXtaox5bI8G3HVNKrQau0VqXWh57AJ9qrUdYt7J/kuB7aoo3F5KzLAvf4f74jWy/i9AL21M/DrZh9+CmhNiCygJM2nTc83o5ef2jq3Bj3YcbhlgvZy8MqnlbZoxmM0tzcpiRksLuigo6ODvzWEQEdwQH49yEsX6LF8PYsVBR8f/bXF1hwYKmh996iRUVvJ2ZyftZWeTW1hLp5MRdISHcFRxMhHPLzgxvqjCRPj+F6rQqgm8Lw6Nn6+sGKkRTaK15JzOTyQcPUq01z3fowITwcKvcVGoOeRV5PP3T08zbOg9PJ0+eGfwM43uPbzXLpJ0OKwffKCCbuvG9EwEv4E2t9QFr1GNrJPi2Y0qpfUBPrXW15bETsF1rHW/dyv5Jgm/TVaVWkjY3GZeOroTeG4EytM3/TIXtqx8He6oh9kTjYF0dXP8RWI/tPnzsfh8XH+wNLbdMSGOqTCbey8ripdRUDldV0c3NjamRkfw7IAD7U+j2GB0Nycn/3B4VBUeOnF5tNWYzX+flsTAzkzWFhShghK8vY0JCuMzPD4cW6pZpqjKRMT+VqpRKgm4KxbOXV4tcV4jmcriykrFJSawtLGSwlxdvx8XR2dU2Jm7blbOLSasmsebQGuL84phzad3437bI2rM6K6VcgEitdaK1arBVEnzbMaXUE8C/gS8BDVwNfKK1/p9VC2uEBN+mMZWbSJlzGMyayEc6YOdu3Q/zon0wmo0UVRWdOMRW/XNbee3xf6Yd7RwbD6wnCLG+Lr4427etNapLjEbmZWQwJzWV7NpaLvD0ZFpkJJf5+WE4jRYggwEa+29dKTCbz7zew5WVvJuVxbuZmWTU1BDs6MidwcHcHRJCJ5ezv+yQudpMxtupVB6sIOiGEDz7eJ/1awpxpkxa80Z6OlMPHcJOKV7s2JGxoaGn9TPemmmt+Wb/N0xaNYn9BfsZ0XkEs4fPJiEgwdqlnRIrt/iOAmYBjlrrDkqpc4DntNZXWKMeWyPBt51TSp0HDLI8XK+13nYa53gXuBzI0Vp3s2x7iboxwzXAQeBOrXWRUioa2AvU38XarLUed7JrSPA9OW3WZLydSkVSOREPRuMcJWtfilOjtaa4urjRGYiPBtZGZiU+2TjY4453Pc4YWF8X3yaNg23LcmtqeDUtjTcyMigyGhnu48PUyEgGn+FsymejxbcxRrOZ7woKWJiZyTf5+ZiBi729GRMaylX+/jidxVZgc42ZzHfSqEgqJ/C6YLz6H3/maiGsbV95OXcnJvJLSQkjfX2ZHxvb4kMFWlqNqYY3fn+DZ9c9S1lNGeN7j+fpwU+3mfG/Vg6+W4GLgJ+11udath2d6EqcGQm+7Ziq+3R1M9BRa/2cUioSCNZa/36K57kQKAM+aBB8hwM/aq2NSqmZAFrrxy3Bd2X9cU0lwffk8lfnUvBdHgHXBuM9QD4ItmeNjYNtSogtrCw84ThYb2fvUw6xnk6ezT4Oti1LqapidmoqCzMzqTKbGe3vz9SoKHp5NM+ETc05xrep0qureS8zk3eysjhSVYWfvT23BwdzT0gIXdzOzmdHc62ZzPfSqNhbTsDVQXhf6HtWriPE6ao1m5mVmsqzR47gZmfHK507c0tQkE3f0DtWbnkuT//8NPO3zsfLyYtnhjzDfeff1+rH/1o5+P6mte6rlNomwbf5SfBtx5RSbwFm4CKtdRellA+wWmvd+zTOFc1xAq1S6mrgWq31zRJ8z47yfWVkLEjF4zxPgm4ObVf/sdq6amP1Ka8Fe7JxsG4Obv/sKux8/DGwvi6+rWIcbFu2r7ycmampfJSdDcCtQUE8FhFB/FkIhmcyq/OZMGvN2sJCFmZmsjwvj1qtGejlxT0hIVwXEIBrEybnOhXaqMn8IJ3ynaX4XxGIz9C20ZokbN9fpaXclZjItrIyrg0I4PWYGIKacfmxtmZXzi4mrprI2kNrifePZ87wOYyMGWntso7LGsFXKfUtcD/wJPADMAW4BngIcGhK70hxchJ82zGl1J9a6/OOuau0/XSmTD9J8F0BLNNaf2Q5bjeQBJQAT2qtN5zs/BJ8j6+2sJaU2Yex97Qn4uFoDE7SutYWZJVlsfrgavIq8k4YYpsyDvZ4Y2AbGw/r6+KLk7311mVtb7aWljI9OZkv8vJwNhgYExLCIxERRNp4V8ecmhrez8ri7cxMkior8bKz4+agIMaEhHBOM7VuA2iTJmtxBmXbSvAbGYDvcP9mO7cQp6rKZOL55GRmpqbiZ2/Pm7GxjA6QlRWgrifSyqSVPLL6EfYX7Gdk55HMHj6bLgFdrF3aP1gp+P4beB74EHABLrHsWgX8t34iWnFmJPi2Y0qp34D+wB+WABxAXYvvuadxrmgaCb6WCbTOB0ZrrbVl5mh3rXW+UqoX8BXQVWtd0sg5xwJjARwdHXtVV8vP/LHMRjNpryVTm1NDxMRoHAMl0LR2Zm1mwdYFTFk7heLqYgDslN3RyZmaOgbWz8UPVwdXad1vhbTWrCsqYnpKCqsLC/Gys+OBsDAeDg8noCVafQ4vhu1PQEUKuEZCzxegQws0+TZCa8364mIWZmTwWW4u1VpzvocHY0JCuDEwEI+TrEncpGuYNNlLMyndUozvJX74jgyQnwvR4n4tLuauxET2VVRwe1AQczp3xtehdXfptYYaUw2v//46z617jrKaMu7vfT9PD3kaX5fWM1zBWl2dlVJuwFPACOoCcH1I01rrOS1djy2S4NuOKaVuBq4HegGLgGupa4H99DTOFc0xwVcpdTswDrhYa11xnOf9DEzWWm850fmlxbdxOZ9lUrypiJA7w3DvIetatna7c3YzduVYfkn9haHRQ5k1fBadfDrh4eQh42BtgFlrVubnMz0lhc0lJQQ5ODApIoJxoaF4NkPAa5LDi+H3sWBq8CvXzhX6LLBa+K1XUFvL4uxsFmZmsrO8HDeDgRsCAxkTGkofD48zCqvarMn5JJOS34rxGeqL36hACb+iRZSbTDx5+DCvpqUR4eTE/NhYRvhJt/uTyS3P5amfnmLBnwvwdvbm2SHPcm+ve1vF+F8rBl9H6ro43wQs5f+DL1rrZ1u6HlskwbedU0rFAxcDCvhBa733NM8TTYPgq5QaAcwBBmutcxscFwAUaK1NSqmOwAagu9a64ETnl+D7TyV/FJP9cQY+Q33xvyLI2uWIE6gyVvHC+heYuWkmnk6ezB4+m9t63iYfzG2E0WxmWW4uM1JS2FVeTrSzM49FRHBncDDOzTyu9aS+ioaKRqZ1do2Cq460bC3HobXm99JSFmZksDQnh3Kzme5ubowJCeGWoCB8TrOVTJs1uV9kU7ypEO9BPvhf3b4mEhIt78fCQsYkJnKoqorxoaHM6NixWXoxtCc7sncwcdVEfjz8I138u/DypS9zaedLrVqTlbo6139u/pq65YsabTASZ0aCbzvWjLM6LwGGAP5ANvA0MBVwAvIth23WWo9TSl0DPAcYARPwtNZ6xcmuIcH376ozqkh95QjOkS6E3ReJspMPd63VT4d/4t6V97K/YD+39riV2cNnE+AmY75sQZXJxHtZWbyUmsrhqiq6uroyNSqK6wMCsD+Ly/mc0McGGjQSNKDgpmZYyLeZlRiNLM3JYWFmJltKS3FSimsDAhgTGsqFXl6nHFy11uQtz6FoXQGe/bwJvDYYZZDfj6J5FRuNPHrwIAszM+ns4sI7cXFc6O1t7bLaLK01Xyd+zSOrH+Fg4UH+FfMvZg+fTbx/vFXqsVLw3QCM01rvbsnrtjcSfNux5pzV+WyT4Pv/TJUmUl8+grnaTOQjHbD3lLvLrVF+RT6T10xm0V+L6OTTiXmXz2NYx2HWLks0gxKjkXkZGbyclkZWTQ19PTyYFhXF5X5+GKzdwtgGWnyP56/SUhZmZvJRdjYlJhOxLi7cExLC7cHBBJ7C2GitNfnf5FL4Qz4efbwIuj5Ewq9oNivz8hiXlERmTQ2PRETwbHQ0Li3ds8NGVRur68b/rn+OitoKZg6byaR+k1q8DmsuZyTOLgm+7Vhzzup8tknwraO1JvO9dMp3lxJ+fxQuHV2tXZI4htaaxTsXM3HVRIqqini0/6P858L/4OLgYu3SxBnKralhbno6r6enU2Q0comPD1MjIxni7d16utS24jG+TVVhMvFpbi4LMzLYVFKCg1Jc6e/PmJAQhvn4NOnmgtaaglV5FKzKq1vm7aZQ6RkjzkheTQ0PHzjAxzk5dHNz4924OHp7ytwaZ0NOeQ5P/fQUo7uMZnin4S1+fQm+tkuCbzvWnLM6n20SfOsU/phP3ooc/K8MxGeITJ7R2hwsOMh939zHmkNruCD8AhZcvoDuQd2tXZY4Q6lVVcxOTWVBZiZVZjOj/f2ZEhnJ+a31Q28rmtX5TO0pL+ftzEw+yMoi32gk2tmZu4ODuTMkhDCnk89iX7A2j/xvcnHv6UHwrWESfsUp01rzSW4uD+7fT5HRyBNRUUyNjMTRWsMZxFknwdd2SfBtxxrM6nwe8D5nMKvz2SbBFyoOlJP+ZgruPTwIvj2s9bQwCWpNtcz+dTbPrnsWB4MDM4bN4N5e92JnkO5vbVliRQUzU1L4KDsbDdwSFMTjERHEu8nnoZZWbTbzZW4uCzMz+bGoCANwmZ8fY0JCGOnre8Ix1YU/55O3PAe3bu4E3x6GwV4Ci2iajOpqxiclsTw/n94eHrwbF0c3d3drlyXOMgm+tkuCbzvXXLM6n23tPfgai2tJmX0Yg4sdkROjMThLoGotNqdtZuyKsezM2cnoLqOZO2IuYZ5h1i5LnIE/S0uZnpLC57m5OBsM3BMSwuSICCKdna1dmgAOVlbyTmYm72VlkVVTQ6ijI3eFhHB3cDDRLo0PKSjaWEDu59m4xrsRcmc4BkcJv+L4tNa8l5XFpAMHqNaa/0ZHMyE83HqT1okWJcHXdknwFW1Cew6+2qRJeyOZ6vQqIiZ2wCn45N37xNlXUl3CtB+m8eYfbxLqEcob/3qDK+OvtHZZ4jRprVlfXMz/kpNZXViIl50dD4SF8VB4+ClNrCRaTq3ZzDf5+SzMzOT7ggI0MMzHhzEhIVzp7/+PrqjFmwvJ+SQLl86uhN4dgcFJQoz4pyOVlYxNSmJNYSEXennxdlwcMa4yn0Z7IsHXdknwbceUUs7AeGAgdetfbATe0lpXWbWwRrTn4Jv7VTZF6woIvjUUj/O8rF2OAL7c+yUPfvcgGaUZPNjnQZ6/6Hk8nDysXZY4DVprVubnMz0lhV9LSghycGBiRAT3hYbiKetxthmpVVW8m5XFO5mZpFZXE+DgwO3BwYwJCSG2QWgp+aOY7CUZOHdwIWxMhPSeEUeZteaN9HSmHjqEUooXO3bk3tBQ68/ULlqcBF/bJcG3HVNKfQKUAh9ZNt0I+Gitr7NeVY1rr8G39K8Sst5Px2uQD4Gjg61dTruXVpLGg989yFf7vqJHUA8WjlpIn7A+1i5LnAaj2cwnublMT0lhV3k50c7OPBoRwZ3BwbI0SRtm0prVBQUszMxkRX4+Rq250MuLMSEhXBMQgIudHaXbSsj6KB3nCBdC743AzkW+3+1dYkUFd+/bx6aSEkb4+jI/NlaGNrRjEnxtlwTfdqyxpYtkOaPWoya7mpSXj+AU4kT4/VEoe7nrbC0ms4k3/3iTJ358AqPZyDNDnmHiBRNxsHOwdmniFFWZTCzKyuKl1FQOVVWR4OrK1MhIrg8MxEHG79mUrOpqFmVl8XZmJgerqvC2t+fWoCDGhITQ4ZCZzA/ScQpxJmxcJHZuEn7bI6PZzKzUVJ45cgRXOzte6dyZW4OCZPLIdk6Cr+2S4NuOKaUWAfO01pstj/sCt2utx1u1sEa0t+BrrjaT+vJhTOUmIh7pgIO3BCxr2ZG9gzErxvB7+u8M7zScty57i44+Ha1dljhFpUYj8zIymJOWRlZNDX09PJgaFcUoPz/pymjjzFqzrqiIhZmZfJ6bS43W9PXw4PHKALotr8Ax0JGw+yKxd5eu7e3J9rIy7tq3jz/LyrjG35/XY2IIbsISWcL2SfC1XRJ82zGl1F4gDkixbIoE9gJmQGute1irtmO1p+CrtSbrwwzK/iohbFwkrrHyu9caKmoreG7dc8z+dTY+zj68fOnL3NT9JmkJaGPyamqYm57Oa+npFBmNDPPxYVpkJEO8veV72Q7l19byYVYWCzMz2VNRwbA8Z179zQuDjz2d7o/GwUtuMtq6arOZ55OTmZGSgp+9PW/ExnJNQIC1yxKtiARf2yXBtx1TSkWdaL/WOrmlajmZ9hR8i9YXkPtlNn6XBeA7zN/a5bRLaw6uYdw34zhUeIi7zrmLFy95ET9XP2uXJU5BalUVs1NTWZiZSYXZzGh/f6ZERtLb09PapYlWQGvNryUlLMzM5ODuQub+6kmxKxy4yZNrOgXj7SAB2BZtLi7m7sRE9lRUcFtQEC937oyvfK/FMST42i4Jvu2QUqo3kKq1zrI8vg24BkgGntFaF1izvsa0l+BbeaSCtNeSceviTshd4SiDtEi1pNzyXCatnsRHOz4i1i+W+ZfPZ0j0EGuXJU5BUkUFM1NS+DA7Gw3cHBjI45GRdHGTzzCiccVGI9/8mU7XT8vJczQxdlAxA6P8GBMSwgAvL+kZYAPKTSb+c/gwr6SlEe7kxPzYWEb6yc1M0biTBV+l1LvA5UCO1rqbZZsvsAyIBo4A/9ZaF1r2TQXuBkzAQ1rrVWf1BYjjkuDbDiml/gSGaa0LlFIXAkuBB4FzgC5a62utWV9j2kPwNZYaSZ19GGWviHikg8w02oK01iz6axGT10ymtLqUKQOnMG3QNJztZVbPtuLP0lKmp6TweW4uTgYD94SEMDkigiiZmVU0UVVyJSnzkim119zav4C9LrV0cXXlnpAQbgsKwl/Wc26Tfios5J7ERA5VVXFfaCgzOnaUpcrECTUh+F4IlAEfNAi+LwIFWusZSqkp1K2S8rhSKgFYAvQBQoG1QKzW2nTWX4j4Bwm+7VDDmZuVUm8AuVrrZyyP/9Jan2PF8hpl68FXmzTp81KoSq4k4uFonMLkw3pLScpPYtzKcfx05CcGRAxgwagFJAQkWLss0QRaazYUF/O/5GRWFRbiZWfH/WFhPBweTqCEFHEaqtKqSJ+XAnbw+3WuzK3JYXNJCY5KcbW/P2NCQxnq7S0TorUBxUYjjx08yILMTDq7uPB2XByDvb2tXZZoA5rS1VkpFQ2sbBB8E4EhWutMpVQI8LPWOs7S2ovWerrluFXU9a789ay+CNEoueXVPtkppey11kbgYmBsg33yb8IK8r/PpfJABUE3hkjobSE1phpe3PQiz69/Hmd7Z+ZfPp97zrsHg5IlbVo7rTXf5OczPSWFX0pKCHRwYHqHDtwXFoaXtOSIM+Ac7kz4+EjS30qh7ycV/HxfV/bH1rIwM5MPs7NZlptLR2dn7gkJ4Y7gYEJkFuBW6Zv8fO5NTCSzpobJERE8Gx2Nq6zPLc6uIK11JoAl/AZatocBmxscl2bZJqxAPiG0T0uAdUqpPKAS2ACglOoMFFuzsPaobFcphWvz8bzAG88+3tYup13YlLKJsSvHsid3D//u+m9eufQVQjxCrF2WOAmj2cynublMT0lhZ3k5UU5OvBETw53BwbjIh1rRTJxCnQl/IIq0N1NIfyOZmPsieTUmhpkdO/JFXh4LMzOZdvgw/zl8mFH+/owJCeFSX1/spBXY6vJqaphw4ACLc3Lo6urKF9260UcmtBOnzl4ptaXB4wVa6wWnea7GfjFId1srkeDbDmmtX1BK/QCEAKv1//d3N1A31le0kJrcGrIXZ+AU7kzA6CBrl2PziqqKmLJ2CvO3zifSK5KVN67kstjLrF2WOIkqk4n3s7N5MSWFQ1VVJLi68kF8PDcEBuJgkBZ60fwcg5wIfyCK9DeTSXszmbB7I3GOdOGmoCBuCgpif0UFb2dmsigri6/y8ohwcuKu4GDuCgkhUsaVtzitNZ/m5vLA/v0UGo08HRXFtKgoHOX3gzg9Rq31+af4nGylVEiDrs45lu1pQESD48KBjOYoUpw6GeMr2gRbHONrrjGT+uoRjEW1RD7SAQdfGZN4tmit+WzPZzz0/UPklOcwoe8Enh36LO6O7tYuTZxAqdHI/IwM5qSlkVlTQx8PD6ZFRTHKz0/GWIoWUVtQQ9obKZgrTITeG4FLtOvf9teYzazIz2dhRgarCwsBGOHryz0hIYzy85MbMy0gs7qa8fv381VeHud7ePBuXBzd3eV3uzh9pznG9yUgv8HkVr5a68eUUl2Bj/n/ya1+AGJkcivrkOAr2gRbC75aa7KXZFK6pZjQMRH/1959h7dZ3m0f/16SPBMntmPHlofshECYZZZSCn0oq0DhAdoCpWmBBmIg7EIfVvtCRwgbysZhFGigjDLKSilQWtKWUgqEsEIIieUhO07seC9J1/uHFDCJExIi6dY4P8fhQ9It+dZPcEXWqWsxbjv9kY6XhjUNnPHcGTy79Fl28+5G/eH17F6xu9NlyUasGh7mpuZmbmlupjMY5IDCQi6pqeFbhYXaWkYSbqRzhObb/QS7Rqis85G3Vf6Yj1sxMMA9ra3cEwjQPDxMWVYWJ5WXc4rXy7T8sX9HvjxrLb9rbeWny5YxGA7zq9pazquqwqMvG2QLbcKqzg8B+wElQBtwGfAk8AjgA/zAMWu3BzXGXArMBILAudba5+NZv2yYgq+khHQLvl3/6mTlI60UH1zCpENLnS4nLQXDQW7+98384q+/wGL5zbd+w1lfOwuPSzM8klXT4CDXNTVR39JCfzjM0SUlXOzz8VXN0ROHBbsi4XekY4SKk6vJn77hzqBgOMyCjg7mBQI8u3o1IeBbhYXM8no5uqSEXM1H32IrBgY49aOPeKGzk30nTuSu6dPZRl8uSIxsSo+vpCYF3wxkjPnpxu631l6fqFo2VToF30H/AE03NZA3LZ+KumqMSz1YsfZm4E1mPT2LNwNv8p2tv8Oth91KTWGN02XJBnzU38/Vfj/3t7URtpYZZWVc6POx/Th97pDkEewJRsJv+zDemVWbNFKnZWiIe1tbuTsQYPngIMUeDyeUlzPL61X7/hLC1nJbczMXffIJxhiumjqV0yoqNPVBYkrBN30p+GYgY8xl0avTga8Cf4rePgL4u7X2FEcK24h0Cb6hviD+61YAFt9Pp+Aer97HWOod7uWyv17Gjf++kdL8Um469CaO2f4YDY9NUm/19DDX7+ex9nZyXC5O8Xq5oLqaGi0OJEkq1Bek+Y5GhgNDlJ9YyfidCjbp98LW8lJnJ/MCAZ5ctYoRa9l7wgRmeb0cM3ky49QL/IWW9PdzypIlLOzq4ttFRdw5fbreKyQuFHzTl4JvBjPGvAB8z1rbE71dADxqrT3E2crWlw7B14YtLfMaGVjaT9XZNeT68pwuKa08t/Q5Zj87m4auBk7d/VSuPPBKCnMLnS5L1mGt5dWuLub6/Szo6GCC280ZlZWcU1VFWbYWeJPkFxoI0XyHn6GmQcp/XEnBLps3FL99eJj7Wlu5KxBgycAAE9xuZpSVcYrXy24FmxakM0kwHOa6piYuW76cPLebG6dN44SyMn2hKXGj4Ju+FHwzmDHmQ2Bna+1Q9HYOsMhau62zla0vHYLv6j+307FgFaXfL6fwG0VOl5M2WntbOWfBOTzy3iNsV7Id9UfUs49vH6fLknVYa3muo4MrGhr4Z3c3pVlZnFdVxezKSiZ6NPJBUktoMERLfSODKwYom1HBhN0nbvY5rLUs7OpiXiDAo+3tDIbD7DZ+PLO8Xn5YVsYE/btgUW8vJ3/4If/t7eXokhJu3XprvDk5TpclaU7BN30p+Gaw6CpzxwJPENlM+2jgYWvtXEcLG0OqB9++D3ppmddIwe4TKfuhV99Ux0DYhrnrzbu48MUL6R/p5+f7/pz/+8b/kePRh6JkEgyHebS9nSv9ft7p66MmJ4ef+XzMLC8nT8M7JYWFh8K03NXIwLJ+Jh/nZeLXCr/0uTpHRpjf1sa8QIB3+vrId7k4bvJkZnm97DVhQsb9zRgKh5nT0MBcv59ij4dbtt6a75eWZtx/B3GGgm/6UvDNcMaY3YB9ozf/bq19y8l6NiSVg+9Ixwj+65bjmeih+txaXNnaamFLfdD+AXXP1LHQv5D9avfjzsPvZJtJ2zhdlowyFA5zX2srV/v9LBscZLv8fC7y+Th+8mTtbSppIzwcJnBPE/1L+mIymsday396epgXCPBQWxt94TA75Oczq6KCH5eVUZyVFaPKk9e/u7uZ+eGHvN/fz4/Kyrhx2jQmZcDrluSh4Ju+FHwlJaRq8A0HwzTd1MBI+zDVP51CdqnmMG6JweAgc1+dy9yFcynIKeDag67lpF1OSrlegPnz4dJLwe8Hnw/mzIEZM5yuKjZ6gkHubGnh+qYmAsPDfLWggEt8Pv63pEQrr0paCo+Eaf1dM33v91JyVBlF/1Mck/P2BIP8YeVK5gUC/Kenhxxj+F5pKbO8Xv4nDfe07g+F+MXy5dzY1ERFTg53brMNh02a5HRZkoEUfNOXgm8Gi87p/R5QC3w6mcha+yunatqQVA2+Kx8N0PXPNXhnVm3y6p8ytldWvMKpz5zKR6s/YsZOM7j+29czedxkp8vabPPnQ10d9Pd/diw/H+rrUzv8rh4Z4aamJm5ubqYzGGT/wkIuqalh/zT8gC6yLhu0BB5opu+dHiYdPpniA2Ib2Bb19jKvpYXft7XRFQqxdV4ep3i9nFhenhaLwr3S2ckpS5awbHCQ0yoquGrqVM1xFsco+KYvBd8MZoxZAHQB/wVCa49ba6/bzPPcAxwOrLTW7hg9Vgw8TCRUrwCOtdZ2Ru+7GDg5+pxnW2v//EXPkYrBt/s/a2h7MEDR/pMoOSL1Alqy6Bjo4Gcv/Ix73r6HKYVTuOPwOzh4q4OdLutLq62Fhob1j9fUwIoVia5myzUPDXFdYyP1LS30hcMcVVLCxT4fe07YvJVuRVKdDVla57fQ+1Y3xYeWMOng0pg/x0AoxGPt7cwLBHi1qwuPMfzvpEnM8no5qLgYd4p9ydQdDPJ/y5ZxZyDAVrm53DV9OvsVafFHcZaCb/pS8M1gxph31wbVLTzPN4Fe4P5RwfdqoMNae6Ux5iKgyFp7oTFme+AhYE+gAngR2MZaG9rA6YHUC75DzYM0/nYFuTV5VJ7mw7hT68NIMrDW8tC7D3HugnPpGOjg/K+fz2X7XUZ+Vr7TpW0Rlwt+8PX5XHHspfhK/PhX+bjkkTn84V8zCIedrm7TLe3v5yq/n/vb2ghby4yyMi70+dh+nD4rSOayYUvbQwF63uii6KBJTDo0fgsyfdjXx12BAPe1tbFqZISanBxmer3MLC+nKgX2t31u9WpO/egjWoaGOLeqil9PmUK+FryTJKDgm74UfDOYMaYeuNlauzgG56oFnhkVfJcA+1lrA8YYL/CKtXZ6tLeXtStHG2P+DFxurf3Xxs6fSsE3NBCi8frlhIctvgum4CnQcK3N9UnnJ5z+7Om8sOwF9qzck/rD69m5fGeny4qJs4+cz9yj6hiX89lY576hfC5+sp6bnkr+sc5v9/Qw1+/nsfZ2sl0uTi4v54LqamrztC+1CETC78pHW+l+bQ2F+xVT8r+T4zrcfygc5qlVq5gXCPBiZycu4NDiYmZVVPCd4mI8SbaY3OqREc79+GN+39bG9vn53LPttnxNI0QkiSj4pi8F3wxmjHkfmAYsB4YAA1hr7Ve+xLlq+XzwXWOtLRx1f6e1tsgYcwvwmrX299HjdwPPW2sf29j5UyX4WmsJ3NNE3/u9VJ1RQ97U1O6dTLSR0Ag3vHYDl79yOW6Xmyv2v4LZX52N25U+vQC982sZb9Yf69xraxg/Y0XiC9pEr65Zw1y/n+c7OpjgdjO7spJzq6rSYn6hSKzZsKX9iTa6FnYycZ8iSo8uw7jiP/Lnk4EB7g4EuLe1lcDwMN7sbH5SXs7JXi9THf5yylrLY+3tnLl0KR3BIBf7fFxaU0NOkgVzEQXf9KWuqMx2qAPPOdZf/jG/fTHG1AF1ANkp8uG68+XV9L0bWdlToXfz/Kf5P8x6ehaL2hZx5PQjufnQm6meWO10WTE33vg367iTrLU839HBFQ0N/KO7m9KsLOZMmcLsigoKtb2IyAYZl6H0u2UYj2HNKx3YoGXyMeVxD79T8/KYM3Uqv6yt5dmODua1tHCl388Vfj8HFhUxy+vlyJKShIfNwNAQZyxdyhOrVrH7+PG8sPPO7Dx+fEJrEBFR8M1g1toxltiJmTZjjHfUUOeV0eNNwOg0UwW0bKC+eqAeIj2+caw1JvqX9rH62XbG71JA4Te1OMem6hnq4ecv/5ybX78Zb4GXx499nKO3O9rpsuIn3wf9Y/zTy/clvpYNCFnLoytXcqXfz6K+Pnw5Odw8bRozvV7NwRPZRMaYyDBnj6HzxdXYkKXsB96E9Px6XC6OLCnhyJISmgYHuae1lbsDAY57/31KsrI4sayMU7xeto3znHxrLfe1tnLesmUMhEJcOXUq51dVJd3waxHJDBrqnIGMMQuttfsYY3qI9Laa0ZfW2s2ebDPGUOdrgNWjFrcqttb+nzFmB+BBPlvc6iVg61Rf3Cq4ZgT/dctx5bvxnVeLK1fhYFP8acmfOOO5M2jubmb2V2czZ/85TMyd6HRZ8bV8PrxeB6FR+xm582HPepji7BzfoXCY+1tbucrvZ9ngINvm53ORz8cPJ08mSx9URb601S+00/H8KsbvOoHyGRWOLHgYspa/dHRwVyDAU6tXE7SWfSdOZJbXy/dLS8mL8ZdaDYODnLpkCX/u7GSfiRO5a/p0pudrJJQkPw11Tl8KvhnIGHMesBB4y1objMH5HgL2A0qANuAy4EngEcAH+IFjrLUd0cdfCswEgsC51trnv+g5kjn42pCl6ZYGhloGqT5vCjnlOU6XlPSau5s5e8HZPP7B4+w4eUfmHTGPvar2crqsxFk+HxZdCv3+SE/vznMcDb29wSB3BgJc39hIy/AwexQUcInPx5ElJbhSbHsUkWTV8dIqVj/TzrivFOD9cSXG49y/rbbhYe5rbWVeIMDHAwNMdLv5UVkZsyoqtngIcthabm9p4aJPPsFay5VTpzK7slLvJZIyFHzTl4JvBjLGXAvsDWwLvAP8E/gH8K+14TTZJHPwbX+ilTV/76T8hEoKdtXKlBsTtmHueOMOLnrxIkbCI1z2P5dx/tfPJ8ut+aJOWD0yws1NTdzc3ExHMMj+hYVc7PNxQFFRXFehFclUnX/rYNWTbYzbfjzlJ1XiynJ2JIW1lr+tWcO8QIA/trczZC1fLShgltfLDyZPpsCzeTPiPurv55QlS3i1q4uDioqo32YbrfguKUfBN30p+GYwY0w2sAeREPz16M8aa+32jhY2hmQNvj1vddN6fzOF3yyi9Ohyp8tJaovbFlP3TB2vNb3GgVMP5I7v3MFWxVs5XVZGah4a4rrGRupbWugLhzly0iQurqnRliIiCbDmH520P9ZK/vRxeGdW4cpOjmkEq0dG+H1bG/NaWnivv5/xbjc/mDyZWV4vXy0o2OiXYcFwmOubmrhsxQpyXS6u32orTiov1xdokpIUfNOXgm8GM8ZMJBJ2vxG9LAQWW2t/4mRdY0nG4DvcNoT/+uXkVORSdUaNo8PWktnAyAC//vuvueaf11CYW8gN376BGTvN0AciByzt7+fqxkbua20lbC0/LCvjQp+PHeK8wI2IfF7Xv9ew8uEAeVvlU3FKNa6c5Ai/EOkFfq27m3mBAA+vXEl/OMxXxo1jltfLjLIyitZZ0f2d3l5OXrKEN3p6OKqkhNu23hpvjqb8SOpS8E1fCr4ZyBhTD+wA9AD/Bl4jsrdup6OFbUSyBd/wYAj/DSsI94fwnT8FT6GG6o7lpU9e4tRnTmVZ5zJO2uUkrjnoGkryS5wuK+O83dPDlX4/j7a3k2UMJ3u9XFBdzRQNQRRxTPcbXbQ92EJubR4VddW4k3BRxO5gkAfb2pgXCPBmby+5LhfHlJYyy+tlzwkTuKKhgSv8foo8Hm7ZemuOKS3Vl5qS8hR805eCbwYyxiwgshDVu0Tm9/4LeNcmcWNIpuBrraX1/mZ6F/VQebqP/K313riu9r52zn/hfB545wGmFU/jzsPvZP8p+ztdVsZ5dc0a5vr9PN/RQYHbzeyKCs6tqqJcvTEiSaHn7W5aH2gmtzqXilN9uPOSL/yu9WZPD/MCAea3tdETCjHO5aIvHGbG5MncOG0aJdnZTpcoEhMKvulLwTdDmchXsjsQmd+7N7Aj0EFkgavLnKxtLMkUfNcuTjLp8FKKD1Dv5WjWWu5fdD/nv3A+XUNdXPiNC7l030vJy1LPYqJYa3m+o4O5fj8Lu7ooycrivKoqZldUUJilkQkiyaZ3cQ+B+5rI8eZSeVo17nGbt6BUovWFQjy6ciV/7uzkR2VlfGfSJKdLEokpBd/0peCb4YwxVUTm+O4NHA5MstYWOlrUGJIl+A580k/TrQ2M23483plVGtI1ytLVSznt2dN4efnL7F29N/WH17PD5B2cLitjhKzlsfZ25jY0sKivj+qcHH5WXc3JXi/5Md6fU0Riq+/9XgL3NpFVmk3l6T48BckdfkXSmYJv+lLwzUDGmLOJBN1vACNEtzKKXi621oYdLG9MyRB8gz1B/Nctx5VlqP7plKQekpZIw6Fhrv3ntfzqb78ix5PDVQdeRd3udbhM8izWks6GwmEeaG3lqsZGPh4YYNv8fC6sruaHZWVku/T/QCRV9C/po+XuRrKKsyLhd6JGaIg4QcE3fSn4ZiBjzPVE9+611gacrmdTOB18bcjSfIefwYYBqs+pJacy17Faksk/G/9J3dN1vNf+Ht/f/vv89pDfUlFQ4XRZGaE3GKQ+EOC6xkZahofZffx4Lqmp4aiSElwaiSCSkvo/7qNlXiOeCR4qZ9eQVaTwK5JoCr7pS8FXUoLTwXfV0yvpfHk1ZT/0MuGrhY7VkSy6Bru4+KWLueONO6iaUMWth93KEdOPcLqsjNAxMsLNzc3c1NRERzDItwoLudjn48CiIg29F0kDA8v7aalvxJXvpuoMH1nFWjRKJJEUfNOXgq+kBCeDb+/iHgL3NDHh64WUHet1pIZkYa3l8Q8e56znz6Ktr42z9zybX+//a8Znj3e6tLTXPDTE9Y2N3NnSQl84zP9OmsTFPh97TZzodGkiEmOD/gGa7/DjynFRObuG7FKFX5FEUfBNXwq+khKcCr7D7cM0Xr+crNJsqs6qwZWVuXMmG7saOeO5M3j6o6fZpXwX5h0xjz0q9nC6rLT3cX8/Vzc2cl9rKyFrOb6sjAurq9lxvL5sEElnQ82DNN3ux7gNVbN9ZJdpGzKRRFDwTV8KvpISnAi+4eEwjb9dQXBNEN/5U8gqzsy5VqFwiFtev4VLX74Ui+VX+/2Kc/Y6B49Lq47G06LeXq70+3lk5UqyjGGm18vPqquZkqetoUQyxVBgkObb/WChcraPHK/WlxCJNwXf9KXgKykh0cHXWkvbgwF6/ttFxaxqxm2Xmb1rbwXeou6ZOt5oeYNDpx3Kbd+5jdrCWqfLSmsL16xhrt/Pcx0dFLjdnF5RwXlVVZTnqLdHJBMNrxyi6TY/NmipPM1HbpXCr6S3pqee4sNrr2UgECDP62XbCy6g6sgjE/b8Cr7pS8FXUoITwbf7X2sI9YUoPqgkYc+bLPqG+7j8lcu54bUbmJQ/iZsOuYljdzhWiyfFibWWBR0dzPX7ebWri5KsLM6tquKMigoKszJzpIGIfGZ41TDNtzUQHgxHwq9PIz8kPTU99RTvXHopoYGBT4+58/L4ypw5CQu/Cr7pS8FXUoLTqzpnkgUfL+D0Z09nxZoVnLLrKVx10FUU5xU7XVZaClnLH9vbmev383ZvL9U5OVxQXc0pXi/5bu0TLSKfGekYoenWBsJ9ISrqqsmbmu90SSIx9+K++zLQ0rLe8byKCg589dWE1KDgm740SU9EAGjrbePcP5/LH979A9MnTedvJ/2Nb9Z8MyHPHbaWkLWEiYTBTbketpZQil9/vaeHpQMDTM/L457p05lRVka2K3MXUBORDcsqzqLqrBqab/PTfKefilnV5E/TZ3NJLwOBwGYdF9kc6vGVlOBEj29fKMRQOLzZgSzVrgdtmE86V7B45bsErWXapG2YUrQVFpOwGtKBC3Abg9uYTb5ekZPDuVVVHFVSglvDyEVkEwS7Rmi+3c9Ixwjek6sYNz0z16CQ9KQeX4knBV9JCU4E30MWLeLPnZ0Jfc4t4QZc0VC1qdeD4RFW9rYyMNLLuKw8fBOqyPfkbvZ5nLj+ZYJmvK67FFpFJIGCPUGa7/AzsnIY70+qGLe9wq+kB83xlXhS8JWU4ETwfaK9Hf/QEG4+CzfJeN31JYLXUHCIKxdeyRULryA/K59rD7qWn+z6E1xGw2xFRFJBqC9I8x2NDAUG8Z5YxfidCpwuSSQmtKqzxIuCr6QELW4VO682vErdM3V8uOpDjt/xeG749g2UjS9zuiwREdlMoYEQLXc2Mtg4QPmPKinYdYLTJYmkPAXf9KXuHZEM0TnQyaw/zeKbv/smg8FBnp/xPA9+70GFXhGRFOXOc1N5WjW5tXm0PtBM93+6nC5JRCRpKfiKpDlrLX949w9sd+t23Pv2vVzw9Qt49/R3OWTaIU6XJiIiW8iV66ayzkfetHzaHmqh67U18X/S5fPhyVp40BW5XD4//s8pGWP+fKitBZcrcjlfzUtiREOdJSVoqPOXs2LNCmY/O5vnP36ePSr2YN4R89ilfBenyxIRkRgLD4cJ3NtE/4d9lH6vjMJ94rT/+vL58HodhPo/O+bOhz3rYcqM+DynZIz586GuDvpHNa/8fKivhxkJal4a6py+FHwlJSj4bp5gOMiNr93IZa9chsEwZ/85nLnnmbhdbqdLExGROAkHw7T+rpm+93opOXIyRftNiv2TPFkL/Q3rH8+vgaNWxP75JKPU1kLDGM2rpgZWrEhMDQq+6UtDnUXSzBstb7DnvD352V9+xgFTDuD9M97nnL3OUegVEUlzLo8L70lVjP9KAaueWknHi6ti/yT9/s07LrIZ/H44fu/5LL+xltDvXSy/sZbj956PX81LYsDjdAEiEhu9w7384uVfcNPrN1E2rozHjnmM7273XYz2mBURyRjGYyg/oZK2B1tY/Ww7Nmgp/nZJ7P4W5Ps20OPri835JaOdecR85h5Vx7icyFjn2tIG5p1SR0kJgIbSy5bRUGdJCRrqvHFPL3maM547g6buJk7b4zTmHjCXibkTnS5LREQcYsOWtocD9LzeRdGBk5h0WGlswq/m+Eoc9c6vZbxZ/4uVXlvD+BkrElKDhjqnL/X4iqSwQE+AsxeczWPvP8YOpTuwcOZC9q7e2+myRETEYcZlKDvOi3EbOl9cjR2xlBw5ecvD79pwu+jSyPDmfB/sPEehV2JivBl7TPOGjotsDgVfiRtjzHTg4VGHpgL/DygEZgHt0eOXWGufS2x1qS1sw9T/t54LX7yQoeAQc/afwwV7X0C2O9vp0kREJEkYl2HyMeUYj2HN3zqwQUvpd8swrhiEXwVdiQcNpZc40uJWEjfW2iXW2l2stbsAuwP9wBPRu29Ye59C7+Z5b+V77Hvvvpz+7OnsUbEHi09fzCX7XqLQKyIi6zHGUHp0GYXfKqbrH52sfLQVG96yaW7aZ1XiZuc5kaHzo7nzI8dFtpB6fCVRDgCWWWsbtNjSlzMYHOQ3f/8NV//jaibkTOC+o+7jx1/5sRavEhGRjTLGUHLEZFweQ8dfVmODlrIfRIZBb65191ltaIjchsTtsyppTEPpJY60uJUkhDHmHuBNa+0txpjLgZOAbuAN4HxrbefGfj/TF7d6efnLnPrMqXzc8TEn7HwC1x18HSX5JU6XJSIiKabjhVWsfr6d8btOoHxGxWaH32TYZ1UknjZlcStjzHnAKYAFFgM/AfKJTPGrBVYAx37R51tJLAVfiTtjTDbQAuxgrW0zxpQBq4i8Wfwa8FprZ47xe3VAHUB2dvbuQ0NDCaw6OazqX8UFL1zAfYvuY6uirbjj8Ds4cOqBTpclIiIprPPl1ax6eiXjdirAe0IlxrPp4dflgrE+OhoD4XAMixRxyBcFX2NMJbAQ2N5aO2CMeQR4Dtge6LDWXmmMuQgostZemJiqZVNojq8kwqFEenvbAKy1bdbakLU2DMwD9hzrl6y19dbaPay1e3g8mTUq31rLA4seYLtbt2P+4vlcss8lLD59sUKviIhssaL9J1F6dBl9i3toubeJ8MimJ1bfBtYY2tBxkTTlAfKMMR4iPb0twJHAfdH77wOOcqY02RAFX0mE44GH1t4wxnhH3Xc08G7CK0piyzqWcfDvD+aEJ09gWvE03qx7kzkHzCEvK8/p0kREJE0UfrOYyceU0/9+L4G7mggPb1r4nTMH8tdZeyg/P3JcJBNYa5uBawE/EAC6rLUvAGXW2kD0MQFgsnNVylgUfCWujDH5wEHA46MOX22MWWyMeQf4FnCeI8UlmZHQCHNfncuOt+/Iv5v+za2H3co/Zv6Dncp2cro0ERFJQxP3LmLyD7z0L+2jZV4j4aEvDr8zZkB9fWROrzGRy/p6LWwlacVjjHlj1E/d6DuNMUVEenenABXAOGPMj5woVDaP5vhKSkj3xa1ea3qNuqfrWLxyMd/d7rvcdMhNVE6odLosERHJAN3/7aLtwRZyfXlU1FXjznM7XZKIYzZhju8xwCHW2pOjt08A9iKyg8l+1tpAdHTjK9ba6QkpWjaJenxFHNQ91M2Zz53J3nfvTcdAB08e9yR/PPaPCr0iIpIwE3afSPmPKxn0D9B8h59Qf8jpkkSSmR/YyxiTbyJ7Sh4AfAD8CTgx+pgTgaccqk82QD2+khLSscf3iQ+e4MznzyTQE+CsPc/iN/v/hoKcAqfLEhGRDNX7bg+tv2smuzybytN8uMdn1sKSIrDJ2xn9EjgOCAJvEdnaaDzwCOAjEo6PsdZ2xLlc2QwKvpIS0in4NnU3ceZzZ/LUkqfYuWxn6o+oZ8/KMRe2FhERSai+D3oJ3NtEVkk2laf78BQo/Epm2ZTgK6lJwVdSQjoE31A4xG3/uY1LXr6EUDjE5ftdznl7nUeWO8vp0kRERD7V/1EfLXc14inKomq2D89E/Z2SzKHgm74UfCUlpHrwXdS6iLpn6ni9+XUO3upgbv/O7Uwtmup0WSIiImMaWNZP87xGPAVuKmfXkFWk8CuZQcE3fWlxK5E46h/p56IXL2L3+t1Z3rmc+d+dz4IZCxR6RUQkqeVtlU/laT5CvSGabmlgZPWw0yWJiGwR9fhKSkjFHt8Xlr3Aac+cxvI1y5m5y0yuOfgaivOKnS5LRERkkw02RlZ6dmW7qJxdQ3ZpttMlicSVenzTl3p8RWJsZd9KfvT4j/j2779NljuLv574V+4+8m6FXhERSTm51XlUza7Bjliabl7BcNuQ0yWJiHwp6vGVlJAKPb7WWn739u+44C8X0DPUw8X7XMzF+15MrifX6dJERES2yFBgiObbG8BC5ek+cir0t03Sk3p805eCr6SEZA++H63+iFOfOZVXVrzCPr59uPPwO9m+dHunyxIREYmZ4ZVDNN/mJzxiqTytmtzqPKdLEok5Bd/0peArKSFZg+9waJirFl7FnFfnkOvJ5ZqDruHk3U7GZTSLQERE0s/wqmGab2sgPBAmf/o4PBM9uCdk4ZnoifxM8OCe6MGV48IY43S5IptNwTd9KfhKSkjG4LvQv5C6p+v4YNUHHLfDcdx4yI2Ujy93uiwREZG4GukYof3xVobbhwl1BwkPhtd7jMk2eCZmfRqEPRNGBeMJnk/vc+Xoi2JJLgq+6UvBV1JCwoPv8vmw6FLo90O+D3aeA1NmALBmcA0X/uVC6t+sp2ZiDbd95zYO2/qwxNUmIiKSRMJDYYLdQYJdI4S6gwS7gtHbwejtEYJdQezI+p85XbmuaBBeG46z1rkdCcquLAVkSQwF3/Sl4CspIaHBd/l8eL0OQv2fHXPnY/es59H+LM5ZcA4r+1Zy3l7n8cv9fsm4bL03ioiIbIy1lvBg+LNg3BUk2D1CaFRIDnYHCXUFsaExAnK++3NDqT1jheUJHoxbw6tlyyj4pi8FX0kJCQ2+T9ZCf8N6h1eSR9nSAXb37k79EfXs5t0tMfWIiIhkCGst4f7QGL3GkaD86e3uIKw7wtqAe5z7017itcOpP7sdDc4FHoxLAVnGpuCbvhR8JSUkNPg+6ALW/3cRtvDbqddz1tfOwuPyJKYWERERWY8NW0J9kYAc6hpZr9f406HXvaH1/6QbPu0h/nwvctbnbrvz3QrIGUjBN30p+EpKSIYe32BuJZ7vNiWmBhEREdliNmQJ9aw7nHr9oBzqC63/y24i4XhC1voLdI0Kyq48rWCdThR805e6rUTWtfOc9eb4Wnc+nl2vcrAoERER2VzGbfAUZuEpzNro48LBMKHu0GfDqdeZezzSNsTA0j7CA2OsYJ1lRq1W/VkgXjcsu3Ld8XqZIrIJ1OMrKcGJVZ2Db12Ie7AFs86qziIiIpKZwsPhzw+n3kAPcnho87Z4Gr2atStbK1g7ST2+6UvBV1JCMu7jKyIiIjKW8GDo02D8+QW6Pr/t04a2eNroAl1rt3jyKCDHg4Jv+tJQZxERERGRGHLlusnOdZM9OWeDj1m7xdNnQ6tH1luga2BZP8HuERhjCrJrnHuMeceez/cqF2iLJ5G1FHxFRERERBLMGIM7z407zw3lGwnI4egWT+utXP1ZUB4ODBHs2cAWT+Pd0SCctcGg7B6vFawl/Wmos6QEDXUWERER2TAbtoR6QwSjc47XXaBr7VzkMbd4coGnYN25x+uvZu0a5077Faw11Dl9qcdXZAzz58Oll4LfDz4fzJkDM7S2lYiIiCQp4zLR7Zc2/vHehizBns/vdzw6KI+sHmFg+QDhMbZ4Mm4zavXqDQTliR5cudriSZKPenwlJSSyx3f+fKirg/7PdjMiPx/q6xV+RUREJDOER8KRPZC7Nr5AV3hwA1s8rV2Qa0JqbfGkHt/0peArKSGRwbe2Fhoa1j9eUwMrViSkBBEREZGUEB6KbvE0qvd4vaHWXSPY4fUzh8lxbXDecU5lzkYXB4sXBd/0peArKSGRwdflgrH+WRgD4fW/1BQRERGRL/DpFk+jF+gatUjXp1s8BSMfwooPmsSkwyYnvE4F3/SlOb4i6/D5xu7x9fkSX4uIiIhIOtjkLZ4GIls8ufK0T7HEllqUxJUxZoUxZrEx5m1jzBvRY8XGmL8YY5ZGL4ucrnO0OXMic3pHy8+PHBcRERGR+DDG4M53k+PNIaswy+lyJM0o+EoifMtau4u1do/o7YuAl6y1WwMvRW8njRkzIgtZ1dREhjfX1GhhKxERERGRVKY5vhJXxpgVwB7W2lWjji0B9rPWBowxXuAVa+30jZ1H+/iKiIiISLxpjm/6Uo+vxJsFXjDG/NcYUxc9VmatDQBELxO/coGIiIiIiGQMLW4l8fYNa22LMWYy8BdjzIeb+ovRoFwHkJ2dHa/6REREREQkzanHV+LKWtsSvVwJPAHsCbRFhzgTvVy5gd+tt9buYa3dw+PRdzQiIiIiIvLlKPhK3BhjxhljCtZeBw4G3gX+BJwYfdiJwFPOVCgiIiIiIplA3WgST2XAE8YYiLS1B621C4wx/wEeMcacDPiBYxysUURERERE0pxWdZaUoFWdRURERCTetKpz+tJQZxEREREREUlrCr4iIiIiIiKS1jTUWVKCMSYMDDjw1B4g6MDzSmZQ+5J4UvuSeFMbk3hyqn3lWWvVOZiGFHxFNsIY84a1dg+n65D0pPYl8aT2JfGmNibxpPYlsaZvM0RERERERCStKfiKiIiIiIhIWlPwFdm4eqcLkLSm9iXxpPYl8aY2JvGk9iUxpTm+IiIiIiIiktbU4ysiIiIiIiJpTcFXMooxptoY81djzAfGmPeMMedEjxcbY/5ijFkavSyKHp8UfXyvMeaWdc71ijFmiTHm7ejPZCdekySPGLevbGNMvTHmI2PMh8aY7znxmiR5xKp9GWMKRr1vvW2MWWWMudGhlyVJJMbvYccbYxYbY94xxiwwxpQ48ZokecS4fR0XbVvvGWOuduL1SOrRUGfJKMYYL+C11r5pjCkA/gscBZwEdFhrrzTGXAQUWWsvNMaMA3YFdgR2tNaeOepcrwAXWGvfSPDLkCQV4/b1S8Btrf25McYFFFtrVyX4JUkSiWX7Wue8/wXOs9b+PRGvQ5JXrNqYMcYDtADbW2tXRYNJv7X28oS/KEkaMWxfk4C3gN2tte3GmPuA+621LyX+VUkqUY+vZBRrbcBa+2b0eg/wAVAJHAncF33YfUTeiLHW9llrFwKDia9WUk2M29dMYG70cWGFXonH+5cxZmtgMvBq/CqXVBHDNmaiP+OMMQaYQCQISwaLYfuaCnxkrW2P3n4R0Kgo+UIKvpKxjDG1RL5J/DdQZq0NQOSNmcgHwU1xb3So4C+if9xFgC1rX8aYwujVXxtj3jTGPGqMKYtjuZJiYvT+BXA88LDV8C9Zx5a0MWvtCHA6sJhozy9wdzzrldSyhe9hHwPbGmNqo6MLjgKq41etpAsFX8lIxpjxwB+Bc6213V/yNDOstTsB+0Z/fhyr+iS1xaB9eYAq4B/W2t2AfwHXxrBESWExev9a6wfAQ1telaSTLW1jxpgsIsF3V6ACeAe4OKZFSsra0vZlre0k0r4eJjJaZQUQjGWNkp4UfCXjRP8g/xGYb619PHq4LTr3ZO0clJVfdB5rbXP0sgd4ENgzPhVLKolR+1oN9ANPRG8/CuwWh3IlxcTq/Sv62J0Bj7X2v3EpVlJSjNrYLgDW2mXR0QSPAHvHp2JJJTH8DPa0tfZr1tqvA0uApfGqWdKHgq9klOhw5LuBD6y114+660/AidHrJwJPfcF5PGtXqIy+iR8OvBv7iiWVxKp9RT8oPg3sFz10APB+TIuVlBOr9jXK8ai3V0aJYRtrBrY3xpRGbx9EZD6nZLBYvoeZ6E4a0RWgZwN3xbZaSUda1VkyijFmHyLDYhYD4ejhS4jMMXkE8AF+4BhrbUf0d1YQWZgjG1gDHAw0AH8HsgA3kYUVfmqtDSXopUgSilX7sta+b4ypAR4ACoF24CfWWn+iXoskn1i2r+h9nwCHWWs/TNyrkGQW4/ew04BzgBEifzNPstauTtiLkaQT4/b1ELBz9By/stb+IUEvQ1KYgq+IiIiIiIikNQ11FhERERERkbSm4CsiIiIiIiJpTcFXRERERERE0pqCr4iIiIiIiKQ1BV8RERERERFJawq+IiIiKcRELDTGHDrq2LHGmAVO1iUiIpLMtJ2RiIhIijHG7Ag8CuxKZC/xt4FDrLXLvsS53NqDXERE0p2Cr4iISAoyxlwN9AHjopc1wE6AB7jcWvuUMaYWeCD6GIAzrbX/NMbsB1wGBIBdrLXbJ7Z6ERGRxFLwFRERSUHGmHHAm8Aw8AzwnrX298aYQuB1Ir3BFghbaweNMVsDD1lr94gG32eBHa21y52oX0REJJE8ThcgIiIim89a22eMeRjoBY4FjjDGXBC9OxfwAS3ALcaYXYAQsM2oU7yu0CsiIplCwVdERCR1haM/BvietXbJ6DuNMZcDbcDORBa0HBx1d1+CahQREXGcVnUWERFJfX8GzjLGGABjzK7R4xOBgLU2DPyYyEJYIiIiGUfBV0REJPX9GsgC3jHGvBu9DXAbcKIx5jUiw5zVyysiIhlJi1uJiIiIiIhIWlOPr4iIiIiIiKQ1BV8RERERERFJawq+IiIiIiIiktYUfEVERERERCStKfiKiIiIiIhIWlPwFRERERERkbSm4CsiIiIiIiJpTcFXRERERERE0tr/B46S5J9mrvuWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,windjan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,windfeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,windmar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Wind Speed Cubed ($\\mathregular{m^3}$/$\\mathregular{s^3}$)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Wind Speed Cubed by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average solar radiation (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f40b5b0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,solarjan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,solarfeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,solarmar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Solar Irradiance (W/$\\mathregular{m^2}$)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Solar Irradiance by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average surface temperature (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f360130>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,tempjan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,tempfeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,tempmar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Surface Temperature ($^\\circ$C)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Surface Conservative Temperature by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average surface salinity (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f29ffd0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,saljan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,salfeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,salmar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Salinity (g/kg)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Absolute Surface Salinity by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average Fraser river flow (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f194d00>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,fraserjan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,fraserfeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,frasermar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Flow (m$^3$s$^{-1}$)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Fraser River Flow by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average surface zooplankton concentration (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f0c5040>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KlSvz2tve4txzz6364osvtveu8iEUfKurqy3HHXfc6PHjx48bPXr0+Oeeey4WAHbu3Bk2YsSIQy+++OLskSNHHnr88cePavlFTJ48eczGjRvtAFBUVBSSnp5+WMsxRx111Jjx48ePGz9+/Lh3333XAQAbNmyImjJlyuhZs2YNHzNmzKE333xz2u9///uklhpuvPHG9P/3//5fUnu1bdq0KfKpp57as27dujgAePHFF6PPOuusES37bNiwIerkk08eCQCvvPJK9OGHHz52/Pjx42bOnDmiurraAgDp6emH3XHHHalHHXXUmBUrVsQ9+OCDwyZMmDBuzJgx488444xDamtrLQDw7bffhk+aNGnshAkTxt1yyy1p/t96/O53v0ueMGHCuNGjR4+/9dZb0/r410BEB2nHkiXwuFz7rfO4XNixZIlJFRERdc2rXpTWl+I/xf/BP374B576+ik8u+VZvLL9Fby16y1s3LsRmwo3YXvZduyt2ouy+jLUN9XDq16zSycKWntWrYp/57jjDnt95Mij3jnuuMP2rFrVJw10p5xySvXatWtjAWD16tXxc+bMqWjZVlNTY7nwwgtzJkyYMG7cuHHjn3vuudiGhgZ54IEH0l5//fW4sWPHjl++fHncbbfdljZ37tzs448/ftT5558/fMOGDVEtrcbV1dWWCy64IGf06NHjR48ePX7lypWxxuPWZ2dndxmyOzJk5vG12+3eN954Y1d8fLy3qKgoZMqUKWMvueSSKgDIzc2NeO65536aOnXq3rPOOmvEM888E3f99ddXdHSutLQ090cfffS93W7Xbdu2hc+dO3fEN998sx0Atm7d6vj666+/HTt2bNPOnTvDzjvvvEN+97vflXo8Hrz66qtxX3311QHfMqxatSr2pJNOqp44cWJjbGys5+OPP7afd955NTfffHN2TU2NJTo62rt69eq4Cy64oKKoqCjkf//3f1M3btz4fXR0tHfRokUpv//975OXLFlSBAARERHezZs37wSA4uJi6+23314OADfddFPa0qVLhy1atKj0hhtuyLz++utLr7nmmoo//elPiS11vPLKK9G7du2K2Lp163ZVxamnnjryzTffjJw5c2Zdn/4yiKjXXEVFPVpPRNSfVBU1jTUorC1EYW0hCmoL2r1fVFuEZm/vPm/aQmywh9phD7XDEeZovW8PtcMR2vlyd46xhdpgkSHTlkM0IPasWhX/7eLF2d7GRgsANJaWhn27eHE2AOTMm9dhTuqOyy67rOLee+9Nveiii6q2b99uX7Bgwb5PP/00EgDuvvvu1BkzZtSsXbt2T3l5ufXoo48ed84559TcddddhZs2bXI888wzuQBw22232bZu3Wr/4osvdkRGRuqGDRuiWs5/5513pkZHR3u+//777wCgrKzMejD1tuh28L1q/VWZ35R+Y++LB20xIWmCc8XsFZ02abfwer1yyy23ZHz++eeRFosFpaWlYfn5+SEAkJ6e3jh16lQXABxxxBHOPXv2hHd2rqamJlmwYEH2d999Z7NYLNi7d2/r/hMnTqwfO3ZsEwCMGTOmKTY21v3JJ5/YioqKQg899FBnSkrKASOxvfjii/E333xzKQDMmTOn4tlnn42fNm2a86STTqpZs2ZNzPz58yvff//9mEceeST/rbfeivrxxx8jJk+ePBYAmpub5aijjmoNppdffnlly/3Nmzfb7rnnnvTa2lprfX299cQTT6wGgK+//jrynXfe2QUAV1999b777rsvAwDeeuut6I0bN0aPHz9+PAA4nU7Ljh07Ihh8iQYPW2qqr5tzO+uJiPqSq9mForoiFNS0H2Zblp3NzgOOjQmPQXp0OtKi0nBSzklIi0xrXU6LSkOyIxke9cDZ7ISz2Yn6pvrW+63rmus7Xa5uqEZRbdF+2+ub6uHpxaC3DNdE+/v+kUfSW0JvC29jo+X7Rx5JP9jgO2XKFFd+fn748uXL40899dRq/20ffvhh9Ntvvx27dOnSFABobGyUXbt2hbV3njPPPLMqMjLygMG6Nm7cGL1mzZqfWpYTExMPZiTsVkOmxffxxx+P37dvX8i2bdu2h4eHa3p6+mEul8sCAGFhYa0vmNVq1Zb1ISEh6vH4Xien0ykt+yxevDg5KSmp+eWXX97t9Xphs9mOatlmt9v365Mzf/788ieeeGJYaWlp6Pz58/e1rau4uNj6+eefR3///fe2G264AR6PR0RE//73v+dffPHFFY8++mjSsGHDPBMnTnTGxcV5VRXTpk2ref3113e39zyjoqJaH3/hwoXDX3rppV3HHXeca+nSpQn/+te/oto7poWq4pZbbin69a9/Xd7Fy0lEJhl7xx3YumjRft2drTYbxt5xh4lVEdFQ4va6UVxXvH+ArSlAYZ3f/dpCVDZUHnBsREgE0qN8AfbI1CMxa/Ss1jDbEmxTI1PhCHOY8Mx8mj3N7Qfnps6DdH1TPZzu/Zf9w3XL/gzXFAway8raDZsdre+pM888s+ree+/NfOedd3aWlpa2ZkpVxUsvvbRr0qRJjf77f/zxxwf8UXE4HO1eC6GqEJH2Nh2Ubgff7rbM9pfq6mrrsGHDmsPDw/X111+PKiws7PKXlpmZ2fjll186ZsyY4Vy1alWc/7kyMjKarFYrHnnkkYSWcNyeyy67rGrx4sXpbrdb5syZ81Pb7c8++2zc+eefv+/555/f27LumGOOGfPOO+9E/uIXv6i9/vrrc5YvXz7swgsvrACAk046qf7222/P+uabb8InTJjQWFtba9m9e3foxIkTG9ue2+l0WrKyspobGxtlzZo18ampqc0AcPjhh9etXLky7le/+lXlihUrWvvqz5w5s+a+++5LW7hwYUVMTIx39+7doWFhYZqens6RsogGiYzZswH4rvV1FRXBlpqKsXfc0bqeiIKXqqLcWd5p62xhbSFK6kqg2L+RxCpWpEalIi0qDaMTRvtaaVsCbdTPLbWxEbH98oGyL4VaQxFjjUFMRIcDwB60Zk/zAcGZ4ZoCSXhiYlNjaekBeSk8MbGpL85/3XXXlcfExHgmT57s8u+mPGPGjJoHH3wweeXKlbkWiwWffPKJ7fjjj3dFR0d76urquvXmO+mkk2oeeuihpBUrfPmzrKzM2hetvoO+xbe5uRlhYWF69dVXV8ycOXPkhAkTxh166KHO4cOHN3R17J133lly0UUXjVizZk3C9OnTa1rW33LLLaVz5sw55NVXX42bNm1arc1m63DkhYiICJ06dWpNbGysJyTkwJdr7dq1Cb/5zW/2uzhv9uzZlc8++2z8mWeeWXfKKadUv/TSSwkvvvjiHsB3ffHjjz++5+KLLx7R1NQkAHDvvfcWtBd877zzzsLJkyePS09Pbxo3bpyzrq7OCgAPP/xw3rx584YvXbo05fTTT6+KjIz0AMD5559f8+2330Ycc8wxYwFf6/WqVat2M/gSDS4Zs2cz6BIFEVVFbVPtfq2xHYXb9q6jTbQntrbGHply5H6tsy3Bdph9GKyWPrkMLiiEWkMRa41FbERsvz1Ge+G6W8G62clwTQdt9A03FPhf4wsAlvBw7+gbbijoi/Mfcsghzb/73e9K267/wx/+ULhw4cKssWPHjldVycjIaPzggw92zZw5s3bJkiWpY8eOHX/77bd3OrDJAw88UDR//vysUaNGHWqxWPTuu+8uvOKKK6quvfbajHXr1sU3NDRYkpOTJ86bN6/8oYceOvD6sQ6IasdzIG/ZsmXPpEmTTO02+9lnn9kWLlyYs23btl4PXX0wPB4PDj300PFr16798bDDDjsgnJqhtrbW4nA4vBaLBcuWLYt74YUX4v/5z3/+2Bfn3rJly7BJkybl9MW5+pLD4dD6+nqzyyAiItpPg7sBRbVF+w8K5dftuGW5vvnA/8Oiw6P3a431v98SblMiUxBm7ZOeiRSA+iJcd7a/meF6fOJ4jB02th9etc6JiFNVzevr34meZrM9q1bFf//II+mNZWVh4YmJTaNvuKHgYK/vHew6yzKDusX3T3/6U+Ljjz+e9Oc//9mUbtabN2+OmD179qiZM2dWDpbQCwCffPKJ/eabb85SVURHR3tWrly5x+yaiKj7vOpFVUMV6pvqER0ejciwSLbUEA0ybq8bJXUlHbbOttyvcB34GTLcGt7aIntEyhH4xahfHBBuU6NSERkWacIzo0AyEC3XTZ6m3nUJbydct7Rcdydc//f0/8bvT/59vz2vYJAzb15FoAfdnhj0Lb40sNjiS9Q7rmYXSutLD7iV1JccsK7MWQa3d/8rECLDIhEdHt3+LSwaMRExHW83blFhUQi1hpr0ChANDaqKfa59+7fOtoTbup+XS+pLDpiD1ipWpESm/NzVODLtgG7HaVFpiIuIG/TX0RINJm3DdX1TPYbZhyE9On3AawmkFt9gNGRbfImIzOLxerDPta/9MFtXglLn/uvqmtqfNcwR6kCSIwlJjiRkxWTh6LSjW5cdoQ7UNdWhprEGNY01qG6sbr1f01iDotqi/ZbbDmbTHluIrcuAHBPedYgOD+l0VjiiQam2sbbTQaFabk2eA8d2GWYf1toae3jK4Qd0PU6PTkeiPZG9M4j6QZg1DGHWsH5tuSZi8CWioKCqqGuqazfIltaXotRpBFpjudxZ3m7QtIoViY7E1vA6Im4EkuxJrcstt+TIZCTaE/tsShBVRX1z/X5BuKNbdUM1app+Xt5dtXu/bd25XivMGtZpC3RriO6iJdoWYmPLFx20Rndjt+ajbe8LqOjw6NbwOi1r2oHX0Ub5rqPllz1ERIGNwZeIhqxmTzPKnGUdh9k2XY0b3O0PBh8THtMaWEcnjMa0rGkHBNkkRxKSHcmIs8WZMlqliCAyLBKRYZFIi0rr9XlUFQ3uhu4F6DYt0AU1BdjeuL11udHT9dAHVrF22brcnVZoR5iDo4QGII/Xg5L6NtfRtoRbv27H+1z7Djg23BreGl4npUzCzJEz252PNio8qp1HJiKiYMPgS0SDhqqiqqGq01ZZ/+7GlQ2V7Z4n1BKK5Mjk1sA6PnF8u62ySY4kJDoSERESMcDP1DwiAluoDbZQG5Ijkw/qXI3uRtQ21fY4RJc5y/Bj5Y+ty85mZ9d1QxAVHtVlC3RXrdBRYVHsqjoAVBUVroou56Mtris+4Dpai1har6MdETcC07KmtTvicbwtnr0JiIio2wZ98LVarUeNGjXK1bK8fv36XWPGjGl34uXJkyePWbJkSd4JJ5zQ9aeoAdLc3IykpKRJl1xySfmjjz7aJ/NmDQYiciaAvwKwAnhCVf/QZvuvAcwzFkMAjAOQqKoVIrIHQC0ADwC3qh49YIXTgGtwN3TaItv21t4clgAQb4tvbXU9LOkwnDL8lHaDbJIjCTHhMfxAPADCQ8IRHhKOYfZhB3Uet9eN2sbuBWj/EF3dUI286rzW9bVNtd16PEeoo09aoYN1ILG6prpuzUfbXo+ABFtCa2vsxKSJ7c5Hm+RI4pcTRESDlIgcNXv27IpXX311N/Bz1jn88MPrP/jgg10dHffpp5/a8vLywi666KLq9rZv3LjRvmLFioSVK1e2O5tPbW2tZdasWSP27t0bbrVacfrpp1f97W9/61G2GvTBNzw83Ltjx47v+up8zc3NCA09uA8rbrcbISHde+leeeWVmOHDhze+9tprcQ8//HCBxXJwXfX6ov6DJSJWAI8COA1APoCvROQ1VW39PanqnwH82dh/FoBbVdV/OPUZqspR6YYgr3pR4ar4eZCnTlplS+tLUdNY0+55IkIikOzwtcq2TPnRUZAdZh8WtCEjGIRYQhBni0OcLe6gzuNV736DhfWkFbqkvmS/bW1bIdsTERLRJ9dBh1vDB8UXNY3uRhTXFXc5H217XzBEhUW1htepmVMPGBQqLSoNKZEpQdW7gogoENlsNu/OnTttdXV1EhkZqevWrYtOTk5uv9XCz6ZNm+ybNm1ytBd8m5ubccIJJzi7ary8/fbbS2bNmlXb0NAgxx9//OgXX3wx+pe//GX7HzTbMeiDb3s++ugj+2233ZbpdDotcXFx7lWrVu3Jzs5uBoCVK1cm3HzzzVl1dXXWZcuW7Z4xY4bztttuSysqKgrNzc0Ni4+Pd5922mk1mzZtcjzzzDO5ADBjxoyRt99+e8nZZ59dO2/evKwtW7Y4GhoaLLNmzar8v//7v0IASE9PP2zu3LnlH3zwQfSpp55a/frrr8d999132wFg27Zt4RdffPGIb7/9dnvbWlevXh1//fXXlyxfvjzx/fffd8yYMaM+KyvrsC1btnw3bNgwDwBkZWVN+OSTT3ZYrVbMnz8/u6CgIAwAHnroodzTTz+9vm39S5YsKbjkkkuGu1wuCwD89a9/zT3ttNPqPR4PrrjiiqzPP/88KjMzs9Hr9eLKK6/cN3/+/MrOXrNemAxgl6r+BAAisgbAbAAdfUExF8DqXj4WDYD6pvpOp99pOxVPe6HAIhYMsw9rDatHpx3dGmzbuzlCHYPiwz4FDotYWsPkwVBVOJud3Q7QNU3GgGKNNdhbtXe/YN122qr2hFpCu9UC3VUrtD3U3u6/KY/Xg9L60i7noy13HvhdZJg1rDXAHpZ0GM445IwD5qNNi0rjdbRERIPQY48h/v77kV5cjLCUFDTdcw8Krr0WBz2v7ymnnFK9du3a2Pnz51euXr06fs6cORWffvppJADU1NRYFixYkLV9+3abx+ORRYsWFV5wwQXVDzzwQFpDQ4Nl7NixkbfffnvR9u3bbf755pprril/8MEHkz/44INd1dXVlgULFmRt3brVDgB333134ZVXXlk1a9asWgCIiIjQiRMnOvPy8sJ6UvegD76NjY2WsWPHjgeAzMzMxg0bNvx00003Zb3xxhu70tLS3MuXL4+744470teuXbsHAJxOp+Xrr7/e8eabb0YuXLhw+A8//PAtAGzdutX+xRdf7IiMjNSlS5cmdPR4Dz30UEFycrLH7XZj6tSpY7744gvblClTXAAQERHh3bx5804A+PDDD6M//fRT29SpU12PP/74sEsuueSAkTfq6urk008/jXr22Wf3VlVVWZ977rn4U089tf7000+vWrVqVezNN9+87/3333dkZGQ0ZWZmumfNmjX8tttuKznjjDPqfvjhh7Azzjhj1E8//XRA/bW1tZaPPvroe7vdrtu2bQufO3fuiG+++Wb7M888E5eXlxe2c+fObwsKCkImTJgw4corr9zX2Ngonb1mvZAOwL8bQj6AKe3tKCJ2AGcCuMFvtQJ4R0QUwOOquqyXdVAH3F43yp3lB07B00GrbEfXWEaFRe03evGxGce2djduG2TjbfHsnkgBQUTgCHPAEeZAalRqr8+jqmj0NHY/QPu1QhfVFWHnvp2t6zsamM2ff/CPDo9GmDUMJXUlKK4rPmAkb4tYkOxIRnp0OnJiczA1Y2q73Y55HS0R0dD02GOIv/VWZDc0wAIARUUIu/VWZAPAwYbfyy67rOLee+9Nveiii6q2b99uX7Bgwb6W4Hv33Xenzpgxo2bt2rV7ysvLrUcfffS4c845p+auu+4q9G94vO2222z++WbDhg2t36DeeeedqdHR0Z7vv//+OwAoKyvb7wNmeXm59d1334399a9/XdKTursdfK/asSPzm/p6e09O3pUJDodzxdix7fbjbtG2q/NXX30V8cMPP9hOPvnk0QDg9XqRmJjY2nJ5ySWXVADAzJkz6+rq6izl5eVWADjzzDOrIiMju5wE8+mnn45fuXLlMLfbLWVlZaFbtmyJaAm+l19+eetIOldeeWX58uXLh02ePDlv/fr1cV999dUBrb0vvvhi7LHHHlsbFRXlvfTSSysPP/zwNLfbnXfJJZdU3H///Wk333zzvlWrVsXPmTOnAgA++eST6B9++MHWcnxdXZ21srLS0rb+pqYmWbBgQfZ3331ns1gs2Lt3bzgAfPTRR5Hnn39+pdVqRVZWlvvYY4+tBYCtW7eGd/aa9UJ7n4I6em1nAfikTTfn41W1UESSALwrIjtUdeMBDyKyEMBCAAgL69EXOgFHVVHTWNPpiMX+t/ZGQAV8XUr9w+rohNH7DfrkPyBUoj0RtlBbu+choq6JCCJCIhAREoEkR9JBnavJ09T966Cbfg7Lk5InHTh9T7TvOtoQy6D/7puIiHrp/vuR3hJ6WzQ0wHL//Ug/2OA7ZcoUV35+fvjy5cvjTz311P26Ln/44YfRb7/9duzSpUtTAKCxsVF27drV7gf5jvLZxo0bo9esWfNTy3JiYmLrt7fNzc04//zzRyxcuLBk/Pjx7Y771JEh97+eqsrIkSNd//nPf3a0t73tN9Mtyw6Ho7VvZkhIiHq9P3fVbGxstADAjh07wh555JHkzZs3b09MTPTMmTMnp6GhofUNExUV1XrQFVdcUfnHP/4xbc2aNbWHHXaYMyUl5YCJMdesWRO/efPmyPT09MMAoLq62rphw4aoc845p3bBggXhhYWFIW+99Vbs4sWLC43nhk2bNm1v7w3gX//ixYuTk5KSml9++eXdXq8XNpvtqJbje/Oa9UI+gEy/5QwAhR3sezHadHNW1ZbnWyoi6+DrOn1A8DVagpcBgMPh6PJLi6Gm0d3Y4VQ87QXaJk/7/7bjIuL2G734pJyT2p2GJ8mRhNiIWLbeEA1BYdYwJNgTkGDvsMMSERFRq+JitBs2O1rfU2eeeWbVvffem/nOO+/sLC0tbc2UqoqXXnpp16RJk/Yb4fDjjz92tD2Hf77xp6odfl695JJLckaMGNFwzz33lPa05m4H365aZgfKxIkTGyoqKkLee+89x6mnnlrf2Ngo27ZtCz/66KMbAGD16tVxs2bNqn377bcjo6KiPAkJCQcE0kMOOaRp+fLldo/Hg927d4du3brVAQCVlZVWm83mjY+P9+Tl5YV8+OGHMSeeeGK7w4Ta7XY98cQTq2+77basRx55ZE/b7RUVFZZNmzZFFhQUbLXZbAoAf/3rXxOef/75+HPPPbd25syZVddff33myJEjXS2hedq0aTV//OMfk37/+9+XAL7Rz6ZOnepqe+7q6mprRkZGk9VqxSOPPJLg8fie4vTp0+ueffbZhBtuuGFfYWFhyBdffBE1d+7ciq5es174CsAoERkOoAC+cHtJ251EJAbAiQAu9VvnAGBR1Vrj/ukA7u9lHYOKV72odFV2az7Z0vpSVDe2O6gdwq3hrS2vKZEpmJg8sd2peJIjkzHMPgxh1uBuDSciIiKi/aWkoKmo6MCQm5KCHrWSduS6664rj4mJ8UyePNnl3015xowZNQ8++GDyypUrcy0WCz755BPb8ccf74qOjvbU1dV1a5Tfk046qeahhx5KWrFiRR7g6+qcmJjouemmm9Jqamqsa9as2dObmodci29ERISuWbPmx5tuuimrtrbW6vF45LrrritpCXFxcXGeI444YmzL4FbtneO0006re/TRRxvHjBlz6JgxY1zjx493AsBxxx3nmjBhgnPUqFGHZmVlNR511FF1ndVy+eWXV7z55ptx559//gGjiT333HNxU6dOrW0JvQBw8cUXV913330ZLpcrd968eRUnnnjiuKVLl+5p2b5s2bK8q6++Omv06NHjPR6PTJkypXbq1Km5bc99yy23lM6ZM+eQV199NW7atGm1NpvNC/haod97772o0aNHHzp8+PCGSZMm1cfGxnq6es16SlXdInIDgLfhm85ohap+KyLXGtsfM3Y9D8A7qlrvd3gygHXGtzghAJ5X1bd6U8dAcDY7u5x+pyXQltWXHXAdHeCbf9R/0KcjU4/scMCnJEcSosKi2CpLRERERL12zz0o8L/GFwAiIuC95x70yfSqhxxySPPvfve7A1pd//CHPxQuXLgwa+zYseNVVTIyMho/+OCDXTNnzqxdsmRJ6tixY8fffvvtRZ2d+4EHHiiaP39+1qhRow61WCx69913F06bNq3+4YcfTh0+fHjDoYceOh4AFi5cWHrbbbd1e5YY6ah7LABs2bJlz6RJkzjlTAfuueee5Orqautf//rXjrr5Drjq6mpLTEyMt7i42HrMMceM++STT3ZkZWV1PayoYcuWLcMmTZqU048l9orD4dD6+vqud+xDZ606C2/uerP9ekId+18T206LbMstwZ7Aa+mIiIiIhgARcarqAd1yB4OeZrP+GtV5MOssy/DTeC+ddtpph+zduzf8X//61/dm1+LvtNNOG1VTU2Ntbm6WX//610U9Cb20v7kT5uKE7BMOCLKJ9kQ4wgbl30MiIiIiIgC+0ZsDPej2BINvL7377rs/ml1De7788sudZtcQKC6bdJnZJRARERERUR/o1gXGREREREREREMVgy8REREREREFNAZfIiIiIiIiCmgMvkRERERERBTQBn3wFZGjzj333OEty83NzYiLi5s0Y8aMkX1xfrvdfkR39z3llFMOOfzww8f2xeMSERERERENJb3NZp9++qnthRdeiOlo+8aNG+1XXnllZmfnmD59+qgxY8aMHzly5KGXXHJJltvds8lrBn3wtdls3p07d9rq6uoEANatWxednJzc3JNzNDf3aPd2lZeXW7/99ltHTU2NdceOHWEHe76e/qKIiIiIiIjM1NtstmnTJvsbb7zRbvBtbm7GCSec4Fy5cmVeZ+dYv379jzt37vzu+++//3bfvn2hK1asiOtJ7YM++ALAKaecUr127dpYAFi9enX8nDlzWuej+uCDD+xHHHHE2HHjxo0/4ogjxm7ZsiUcAJYuXZowc+bMESeffPLI6dOnj66urrZccMEFOaNHjx4/evTo8StXroxtOceNN96YPmbMmPGTJk0am5eX1+4UT88++2zcqaeeWnXeeedVPP300/EA8Itf/GKE/zcXc+bMyVm5cmWs2+3GNddckzFhwoRxo0ePHv/nP/95GABs2LAhasqUKaNnzZo1fMyYMYcCwKmnnnrIoYceOm7kyJGHLlmyZFjLuf7v//5vWE5OzoTJkyePufjii7Mvv/zyLAAoLCwMOeOMMw6ZMGHCuAkTJox75513OKFsP6lobkZ5UxNq3W40eb1QVbNLIiIiMl3++vV4b/p0vD5yJN6bPh3569ebXRIRteeHx+LxStpheN5yFF5JOww/PBbfF6ftLJvV1NRYLrzwwpwJEyaMGzdu3PjnnnsutqGhQR544IG0119/PW7s2LHjly9fHnfbbbelzZ07N/v4448fdf755w/fsGFDVEurcUe5LT4+3gsAzc3N0tzcLCLSo7qHxDy+l112WcW9996betFFF1Vt377dvmDBgn2ffvppJABMmjSp4csvv9wRGhqKV199Neo3v/lNxttvv/0jAPz73/+O3Lp167fJycme6667Lj06Otrz/ffffwcAZWVlVgBwuVyW4447ru7hhx8uuPbaazMefvjhxD/96U9FbWtYu3Zt/D333FOYlpbWfMEFFxzywAMPFF900UUVL7zwQtxFF11U3dDQIJ988kn0008/vfcvf/nLsJiYGM8333yz3eVyyTHHHDN21qxZNQCwdetWx9dff/3t2LFjmwBg1apVe5KTkz11dXVyxBFHjL/00ksrGxoaLEuWLEn997///V1sbKx36tSpow899FAXAFxzzTWZt912W8kZZ5xR98MPP4SdccYZo3766advB+Y3EVwu3b4db1bsP+d3uAjCLRaEWSyt91tvIr71A7QtzFi29PAfPRERUW/lr1+PrYsWweNyAQBchYXYumgRACBj9mwzSyMifz88Fo/Nt2bD2+Br6GwoCsPmW7MBAKOurejs0K50ls3uvvvu1BkzZtSsXbt2T3l5ufXoo48ed84559TcddddhZs2bXI888wzuQBw22232bZu3Wr/4osvdkRGRuqGDRuiWs5/5513praX2wBg2rRpo7Zu3eo48cQTq+fPn1/Zk7q7HXxLVhdmNhY32nty8q6Ep4Q7k+emddqkDQBTpkxx5efnhy9fvjz+1FNPrfbfVlFRYb3ooouG79mzJ0JEtLm5uTUFTJ8+vSY5OdkDABs3boxes2bNTy3bEhMTPQAQGhqqF198cTUAHHXUUfXvvfdedNvHz8vLC9m7d2/46aefXmexWBASEqJfffVVxAUXXFD9m9/8JsvlcsnLL78cM3ny5NrIyEh97733onfs2GF/7bXX4gCgtrbW+t1330WEhYXpxIkT61tCLwD88Y9/TH7jjTdiAaC4uDj022+/jSgsLAydMmVKbUvt5513XuX3338fAQCffPJJ9A8//GBrOb6urs5aWVlpiYuL83brRaduuz4tDTPj49Ho9aJR1fez5aaKJr/7/tvqPR5UdLCtyVjuy19WiEiHobizwNyf20IsQ6IzCRER9dCOJUtaQ28Lj8uFHUuWMPgSDSbb7k9vDb0tvA0WbLs//WCDb2fZ7MMPP4x+++23Y5cuXZoCAI2NjbJr1652LxM988wzqyIjIw/oUtlRbgOAjz/++Aen0ynnnXfeiNdffz36vPPOq+lu3UOixRfwvTD33ntv5jvvvLOztLS0te7f/va36SeeeGLtu+++++POnTvDTj755DEt2+x2e2u+UFW01xweEhKiFuNDekhICNxu9wE7Pf300/E1NTXWzMzMwwBf2Hz22Wfjly5dWnjsscfWvvLKK9EvvPBC3Ny5cyuMx5IHH3wwd86cOfv9IjZs2BDlX9OGDRui/vWvf0Vt2rRpR1RUlHfy5MljXC6XpbMutaqKTZs2bW/vTUJ96+xhw7reqZfcnYTizgJzT7Y1tdmvxuPpcFujKtx92JXbAhwYiNsE5r7e1lErfMu2MJF2/wYQEVH3uYoO6BTX6XoiMklDcftjEnW0voc6ymaqipdeemnXpEmTGv33//jjjw+4PNPhcLTbFtRRbmtht9v17LPPrlq3bl1svwTf7rTM9qfrrruuPCYmxjN58mSXf1N4TU2NNSMjowkAHn/88Q6TykknnVTz0EMPJa1YsSIP8DWZ+3970JmXXnopft26dT+ceuqp9QCwY8eOsNNPP3300qVLCy+++OKKJ598cti2bdsca9eu3QMAp512WvXf//73xLPPPrs2PDxct27dGp6Tk3PARd9VVVXWmJgYT1RUlPfrr7+O2LJliwMApk+fXn/XXXdllpWVWWNjYz3r16+PGzdunAsApk2bVvPHP/4x6fe//30J4BshberUqa6256bBLcRiQQgAh9Xa5b4DxWuE4fZCcWeBuattTR20mDd6vah2uzvc1nJcX2qv1bqrwNzf3dbZVZ2IzKaqaFKFy+OBy+uF0+tt977L64U9KQnWkpIDztGclISH8vLQ8hdNAIiI72cXy+jGPoF8zH77D6Vj+P/X4BaR0oSGogNDbkRKUzt791hH2WzGjBk1Dz74YPLKlStzLRYLPvnkE9vxxx/vio6O9tTV1XWrS2B7uS0sLEyrqqqs2dnZzc3NzXjrrbdijj/++Nqe1DxkWnwPOeSQ5t/97nelbdf/9re/Lb766quHL126NGX69OkdJv4HHnigaP78+VmjRo061GKx6N133114xRVXVHX1uDt37gwrLCwMO/nkk+tb1o0dO7YpMjLS8/777zvOO++8mmuvvXb4qaeeWhUREaEAcOutt5bv2bMn/LDDDhunqhIfH9/8j3/848e2554zZ071smXLEkePHj3+kEMOaZg0aVI9AAwfPrz51ltvLTrmmGPGJSUlNY8ePdoVExPjAYBly5blXX311VmjR48e7/F4ZMqUKbVTp07N7daLSNQJiwhsVitsXe86YFQVze20aHcUpjvqft6TbW27qrd3XF92VQ8TQYTFApvFApvV2nq/3Z99uJ2Bm2hwcxtBs/Xm8fhCaDv32wuoTr/7bZf322acq7tfM54waxZueOYZRDT9/Nm5ISwMj8yahY0/HvBRh4LAwQZsdLDP7RkZuDM7eyCfSmA57J6C/a7xBQBLhBeH3VPQF6fvKJv94Q9/KFy4cGHW2LFjx6uqZGRkNH7wwQe7Zs6cWbtkyZLUsWPHjr/99ts77SLSXm47+eST637xi1+MbGpqEq/XK8cff3zNr3/967Ke1CyddavdsmXLnkmTJpX35ITUN6qrqy0xMTHe5uZmnHHGGSOvvPLK8ssvv7yqvx93y5YtwyZNmpTT34/TUw6HQ+vr67vekWgAuDsJxT3pmt7gd3O189Pl8XS4rcF7cPE7VMQXtvshVHe23crATUOUqrb+++ssVB5MQPW/39zLHi9WADarFXa/L9RsFotvuZ37NosFdr/7bZf322act+6NN5D3l7+gsagI4ampGHHbbUiaNcv3Ohmvlbbc72I5kI5BN8/LY35e3m//NvucGR+Pc/rxsrOOiIhTVQflrCk9zmY/PBaPbfeno6E4DBEpTTjsnoKDvb53sOssywyZFt9g8+tf/zpt48aN0Y2NjXLiiSfWXHrppVVm10REPoOhq7oaAbqzYNxZcO4qVNc0NXW4/WC0BO7+aslu+5OBO7A19yBIHmxAPZj3vn+obBtKk8PCOgyonYbQDkJpqGUABhecMwfj5szp/8chooMz6tqKQA+6PcHgO0gtW7Ys3+waiGjwEhFEWK2IsFoRO4CP638tYG9DdWfba5ub293eF4G7v7uPR/gFkpZtwRa4vaoH3dLZk4DarYE62uHf46FteIwJCUFKOwG1t62mERYLr4UkIhoEGHyJiKjbxG/6rIHUncDdVajubHtZc3Pr9rbbDmaItZD2Wrj7IXS33dYypVjL69YfXXHbC6i9HZBOgE7DY2xISLutm70NpZxyjYgo+HQVfL1er1csFgunzgkCXq9XgD4dt4eIqE+YHbgPJlT7b2+7rtwvcLc95mADd6jIQQX3MJEOu9nGtwminYXSzgJqy7GcboyIqFuYzTrRVZbpKvh+U1ZWNj4xMbGaL3Dg8Xg8FovF4hUReL1eKSsriwHwjdl1ERENFv6BOyZk4DpJtYxofjChusnrRUQvQymviyYiGpSYzTrQnSzT6f/ibrf76uLi4ieKi4snAGC/oADgdDodLpfL4Xa7w+EbNE8sFosnNDTUGRISsjkiIuJqs2skIgp2IoIwY+7nGLOLISKiQYHZrFNeAN+43e4Os0yn0xlRYBGRfwF4D8B6AN+oqtdYHw9gBoBLAKxT1efMq7J9nM6IiIiIiPrbYJ7OiA4Og28QEZFQVW0+2H3MwOBLRERERP2NwTdwcVTn4HJXJ4OHqKr+fjCGXiIiIiIiooPBvuHBpb6dmwJYAOC3JtZFRERERDToicgKESkVkQMGURKRO0RERWSY37q7RGSXiOwUkTMGtlryxxbfIKKqD7bcF5EoADcDuArAGgAPdnQcEREREREBAFYCeATAM/4rRSQTwGkAcv3WjQdwMYBDAaQBeE9ERquqZ8CqpVZs8Q0yIhIvIv8PwFb4vvg4UlV/q6qlJpdGRERERDSoqepGABXtbPo/AL8B9ps+fTaANaraqKq7AewCMLn/q6T2MPgGERH5M4CvANQCOExV71PVyl6cp8MuHsZ2EZGlRreOrSJypN+2M42uHrtE5M5eP5l+lr9+Pd6bPh2vjxyJ96ZPR/769WaXRERERESDkIicA6BAVbe02ZQOIM9vOd9YRyZg8A0ut8PXzeK/ARSKSI1xqxWRmh6cZyWAMzvZPhPAKOO2EMDfAUBErAAeNbaPBzDX6AIyqOSvX4+tixbBVVgIqMJVWIitixYx/BIREREFvhAR2eR3W9jZziJiB7AIwD3tbW5nHafUMQmv8Q0iqtonX3So6kYRyelkl9kAnlHfXFmfi0isiKQCyAGwS1V/AgARWWPs+11f1NVXdixZAo/Ltd86j8uFHUuWIGP2bJOqIiIiIqIB4FbVo3uw/yEAhgPYYsyekgHg3yIyGb4W3ky/fTMAFPZVodQzbPGl/tBRt44h0d3DVVTUo/VEREREFJxUdZuqJqlqjqrmwPf59khVLQbwGoCLRSRcRIbD1xvySxPLDWoMvtQfOurW0aPuHiKysKWbidvt7rPiumJLTe3ReiIiIiIKDiKyGsBnAMaISL6ILOhoX1X9FsCL8PVufAvAf3FEZ/Mw+FJ/6KhbR4+6e6jqMlU9WlWPDgkZuF75Y++4A1abbb91VpsNY++4Y8BqICIiIqLBR1XnqmqqqoaqaoaqPtlme46qlvstL1bVQ1R1jKq+OfAVUwsGX+oPrwG43Bjd+VgA1apaBN+I0qNEZLiIhME3r9lrZhbanozZszFx8WLY0tIAEdjS0jBx8WJe30tERERENESJb/whCgYi0mnIVNVzunme1QBOAjAMQAmAewGEGud4THxX9j8C38jPTgDzVXWTcexZAP4CwApghaou7s5jOhwOra+v786uRERERES9IiJOVXWYXQf1PQbfICIiZfANLrUawBdoc82tqv7LjLq6g8GXiIiIiPobg2/g4nRGwSUFwGkA5gK4BMAbAFYbF94TEREREREFJF7jG0RU1aOqb6nqFQCOBbALwIcicqPJpREREREREfUbtvgGGREJB/AL+Fp9cwAsBfCKmTUREQ016lWoRwGP76d6YPz0X+dbv/+y/z4dHONVwG1s9yrUbezTct/rOw5uba1D3cZ2v3NabVYkX5KKsKRws18uIiIi0/Ea3yAiIk8DmADgTQBrVPUbk0vqNl7jSxRYhkJwbFuH/7qOZyDvO2IVwApIiEAsYiz7fvpuaLPsvx1w/eCEhFmQcVM2QmND+79gIqIAwGt8AxeDbxARES+AlvTo/4sXAKqq0QNfVfcw+BLtb//g2FFY8wuO7QVABsdOg+OB6+Tnc7Z7nN8xFvE9rtV47BDjOL/1rftYjFr967QAvgHye68hz4WCR3MREhuCjBuzYXWwkxcRUVcYfAMXgy8NCQy+FGicP9SjamNFa6jsOsRiv2UGx/4PjoHAuasehY/nITw9HOnXZcMSzqE9iIg6w+AbuBh8aUhg8KVA0ljYgLyle2EJE4TEhTI4Ur+q21aLoqfyYR/lQOqvMmAJYfglIuoIg2/gYvANQiKyDcBWv9s2AFeo6mJTC+sEgy8FCk+dG7n/twfqVmTdmoMQXntJA6DmyyqUrC5C5KQopFyeDrHwSw0iovYw+AYufu0bnE4EsByAC8DFAL6Bb6RnIupH6lYUrSyAp8aNtKsyGHppwERPjsWw2Umo21KL0peKwS+9iYgo2HCkiyCkqhUAPjRuEJFRAP7bxJKIAp6qovSVYrh+dCL50jREZNvMLomCTNxJCfDUe1D53j5YI60YdlaS2SURERENGAbfICQio1T1h5ZlVf1BRCaaWRNRoKv+uBI1n1Uh7pQERB8VY3Y5FKQSzkr0hd9398FqtyLupASzSyIiIhoQDL7BaZmIHAKgAL5rfCMAfCMiDlXlhbREfcy5sx5lr5bAcWgkEs5KNLscCmIigqQLUuB1elC+vhRWuxXRk2PNLouIiKjfMfgGERER9ZlhLGcBOBzAJOPn18YuY8yrkiiwNJU1oejpfIQlhyPl0jQOKkSmE4sg+dI0eFz5KHmhCBa7FZEToswui4iIqF9xcKvg8oGI3GgEXqhqrqq+BuCPAP4G4HMAj5pZIFEg8bg8KHwiD7AI0hZkwBJhNbskIgCAJcSCtKsyEJ4RgeKnC+Dcxc4+REQU2Bh8g8uZADwAVotIoYh8JyI/AfgBvtGdH1TVpaZWSBQg1KsofqYAzeVNSL0yHaEJYWaXRLQfS7gF6QszEZoQiqIn89GQ32B2SURERP2G8/gGKREJBTAMgEtVq0wup0ucx5eGmrL1Jaj6sAJJF6YgZmqc2eUQdai5qhn5S/dAmxUZN2YjLCnc7JKIiEzDeXwDF1t8g5SqNqtq0VAIvURDTc2XVaj6sAIx0+IYemnQC40NRfq1WQCAgsfy4K5qNrkiIiKivsfgS0TUh1y7nSh9sRi2UXYknptsdjlE3RKWFI60hZnwOj0oeCwXnnq32SURERH1KQZfIqI+0lzZjKIV+QiJC0HqFRkQK0dwpqEjItOG1Ksz0LyvGYXL8+Bt9JpdEhERUZ9h8CUi6gPeRi8Kn8iDuhVpV2fC6uAIzjT02Ec6kHJ5OhpyG1C0Ih9eN8MvEREFBg5uFYREJBzAHAA58JvLWVXvN6umrnBwKxrM1KsofroAddtqkfarTDjGRZpdEtFBqf6iCqVrihB5eBRSLkvn/NNEFDQ4uFXgCul6FwpA6wFUA9gMoNHkWoiGvIp3ylG3tRbDzkli6KWAEDMlFl6nB+WvlaLUVoykC1MgwvBLRERDF4NvcMpQ1TPNLoIoENT+pwYVb5cjanIMYk+KN7scoj4TNyMBHqcHle/tgzXSimFnJZldEhERUa8x+AanT0XkMFXdZnYhRENZQ54LJc8XIiLHxhYxCkgJZyXCU+dB5bv7YLVbEXdSgtklERER9QqDb3CaBuBKEdkNX1dnAaCqOtHcsoiGDneNG0Ur8mF1WJF6VQYsIRwrkAKPiCDpwhRft+f1pbA6rIg+JtbssoiIiHqMwTc4zTS7AKKhzNvsRdGKfHicHmTcmIOQKP4ppcAlFkHyZWnwLM9HyZoiWGxWRE6IMrssIiKiHmETRRBS1b0AYgHMMm6xxjoi6oKqovTFYjTsdSF5bhoiMiLMLomo31lCLEi7KgPhGREofroAzl0cZZ+IiIYWBt8gJCI3A1gFIMm4PSciN5pbFdHQUPVhBWo3VSP+jGGIOjza7HKIBowl3IL0X2UiNCEURU/moyG/weySiIiIuo3z+AYhEdkK4DhVrTeWHQA+6+41viKyAsDZAEpVdUI72+cB+K2xWAfgOlXdYmzbA6AWgAeAW1WP7s5jch5fGgzqv6tD4RN5iJwYhZTLObcpBafmqmbkL90DbVZk3JSDsMQws0siIuoznMc3cLHFNzgJfMGzhcdY110rAXQ2HdJuACcaQfr3AJa12T5DVQ/vbuglGgwaixtR/GwBwtPCkTw3jaGXglZobCjSr80CABT8PRfuqmaTKyIiIuoag29wegrAFyJyn4jcB+BzAE9292BV3QigopPtn6pqpbH4OYCMg6iVyHSeejeKnsyDhApSF2TCEs4/nRTcwpLCkbYwE16nBwWP5cJT7+n6ICIiIhPx01sQUtWHAFwFX3itBDBfVf/STw+3AMCb/g8P4B0R2SwiCzs7UEQWisgmEdnkdrv7qTyizqlHUfR0AdyVbqRelYHQuFCzSyIaFCIybUi9OgPN+5pRuDwX3kav2SURERF1iNf4Uq+ISA6ADe1d4+u3zwwAfwMwTVX3GevSVLVQRJIAvAvgRqMFuVO8xpfMUvpyMao/rkTy3FRET441uxyiQaduWy2KnsqHfbQDqVdzTmsiGtp4jW/g4v9OQUREPjZ+1opIjd+tVkRq+vixJgJ4AsDsltALAKpaaPwsBbAOwOS+fFyivlT1SSWqP65E7Ix4hl6iDkQeFoWki1Lh3FmPklWFUC+/UCciosEnxOwCaOCo6jTjZ1R/Po6IZAF4BcBlqvq933oHAIuq1hr3Twdwf3/WQtRbzl31KHulGPZxDgw7O8nscogGtZgpsfA6PSh/rRSltmIkXZgCEQ4AR0REgwdbfIOQiPyxO+s6OX41gM8AjBGRfBFZICLXisi1xi73AEgA8DcR+Y+IbDLWJwP4WES2APgSwBuq+tZBPRmiftBc3oSipwoQlhiGlMs4bRFRd8TNSEDcKQmo+awK+94sM7scIiKi/fAa3yAkIv9W1SPbrNva3Xl8zcBrfGmgeBo8yP/rXrhrmpF5y3DOUUrUA6qK0heLUfN5FYbNTkLcSQlml0RE1CO8xjdwsatzEBGR6wBcD2CEiGz12xQF4FNzqiIaPNSrKHm2EE2ljUi/Nouhl6iHRARJF6b4uj2vL4XVYUX0MbFml0VERMQW32AiIjEA4gA8AOBOv021qtrhvLyDAVt8aSCUv16Kyvf3IXFOMmKnxZtdDtGQ5XV7UbgsD64fnUidn4HICf06tAQRUZ9hi2/g4jW+QURVq1V1j6rOBVAD3zW32QAmiMgJ5lZHZK6aTdWofH8foo+LRczxcWaXQzSkWUIsSLsqA+EZESh+pgCuH51ml0REREGOwTcIicjVADYCeBvA/xg/7zOzJiIzNex1ofSFIthG2pE0h6PREvUFS4QV6b/KRGh8KAqfyENDfoPZJRERURBj8A1ONwM4BsBeVZ0B4AgAHIKTglJzVTMKn8yDNToEqVekQ6wMvUR9xRoZgrRrs2CxWVD4eC6ayprMLomIiIIUg29walDVBgAQkXBV3QFgjMk1EQ04b5MXRU/mw9ukSLs6E9ZIjvdH1NdCY0ORfm0WoEDB33Phrmo2uyQiIgpCDL7BKV9EYgG8CuBdEVkPoNDUiogGmKqiZE0RGgsakHJpGsJTw80uiShghSWFI+2aTHidHhQ8lgtPvcfskoiIKMhwVOcgI76LFzNUNc9YPhFADIC3VHXQ9kHjqM7U1yreKce+N8uQcHYi4k8ZZnY5REHBuasehY/nITw9HOnXZcMSzu/fiWhw4ajOgYv/4wQZ9X3T8arf8r9U9bXBHHqJ+lrd1hrse7MMUUdFI+7kBLPLIQoa9pEOpFyejobcBhQ9lQ9188t3IhpaRGSFiJSKyDd+6/4sIjtEZKuIrDN6VrZsu0tEdonIThE5w5SiCQCDb7D6XESOMbsIIjM0FjSgeFUhwrMikHRRKkdwJhpgkYdFIemiVDh31qN4VQHUy/BLREPKSgBntln3LoAJqjoRwPcA7gIAERkP4GIAhxrH/E1ErB2dWERuEBHOqdhPGHyD0wwAn4nIj8Y3U9tEZKvZRRH1N3et2zeCs82KtKsyYAnln0AiM8RMicWwc5JQ959alL5UDF52RURDhapuBFDRZt07quo2Fj8HkGHcnw1gjao2qupuALsATO7k9CkAvhKRF0XkTOG3832KQ5gGp5lmF0A00NStKHoqH546DzJuyEZITKjZJREFtbgZCfDUe1D5z30IibQi4awks0siIgKAEBHZ5Le8TFWX9eD4qwC8YNxPhy8It8g31rVLVf9bRH4H4HQA8wE8IiIvAnhSVX/sQQ3UDgbf4HS9qv7Wf4WI/BHAbzvYn2hIU1WUvlSEht0upFyejogsm9klERGAhF8kwlPvQcW7+2BxhCDuxHizSyIicqvq0b05UEQWAXADWNWyqp3dOu3ioqoqIsUAio1zxQF4SUTeVdXf9KYu8mE/v+B0Wjvr2ApMAatqYyVqvqhG/GkJiDoi2uxyiMggIki6MAWRE6NQ/moJar6qMrskIqJeEZErAJwNYJ7+fP1GPoBMv90y0MkUoiJyk4hsBvAnAJ8AOExVrwNwFIA5/VJ4EGGLbxARkesAXA9ghN81vQIgEsCnphVG1I/qd9ShfH0JHIdFIf7MRLPLIaI2xCJIviwNnmV5KFlTBIvNisgJUWaXRUTUbSJyJnw9J09UVaffptcAPC8iDwFIAzAKwJednGoYgPNVda//SlX1isjZfVx20OE8vkFERGLg6y7xAIA7/TbVqmpF+0cNDpzHl3qjqbQRef+3ByHxoci8KYdzhhINYt4GD/L/noumokakX5MF2yF2s0sioiDU1Ty+IrIawEnwhdQSAPfCN4pzOIB9xm6fq+q1xv6L4Lvu1w3gFlV9sxs1JAGIaFlW1dxePRnaD4NvEBKRCADnA8iBX6u/qt5vVk1dYfClnvI4Pcj7yx54XR5k3jocofEczIposPPUuZH38F54atxI/69sRGREdH0QEVEf6ir49vNjzwLQ0jpcCiAbwHZVPdSMegINmz+C06vwDa/uBlDvdyMKCOpRFD9dgOaKJqTOz2DoJRoirJEhSL82C5YICwofz0VTWZPZJRERDaT/B+BYAN+r6nAAp8B3rS/1Abb4BiER+UZVJ5hdR0+wxZd6omxdMao2ViLpolTEHBtrdjlE1ENNpY3IX7oXEmZB5k3ZCInll1dENDBMbvHdpKpHi8gWAEcY1/Z+qaqdzf1L3cQW3+D0qYgcZnYRRP2h+vNKVG2sROwJcQy9RENUWFI40q7JhMfpQcHjefDUe8wuiYhoIFSJSCSAjwCsEpG/wtdDk/oAW3yDkIh8B9+ocj8BaIRvZGdV1YmmFtYJtvhSd7h+dCL/73thH+lA2q8yIdb2ps8joqHC+UM9CpflITw9HOnXZXOAOiLqdya3+DoAuOBrnJwHIAbAKlXd1+mB1C0MvkFIRLLbW9926PTBhMGXutJc0YS8h/bAYrci89YcWG1Ws0sioj5Qt60WRU/lwz7agbSrMyEh/EKLiPqPycE3Fr7GKcB3nW+1GXUEKn51GpxyAUwHcIURdhVAsrklEfWet9GLwifzoR5F2tUZDL1EASTysCgkXZQK5856FD9fCPXyC3siCiwiEiYiKwHsAbAMwHIAe0RkhYiEmVlbIGHwDU5/A3AcgLnGci2AR80rh6j31KsoXlWApqJGpFyRjrCkcLNLIqI+FjMlFsPOSULd1zUoe7kY7K1GRAHmvwGEAshU1SNU9XAAWfBNO/o7MwsLJCFd70IBaIqqHikiXwOAqlby2yQaqva9VYb6bXUYdm4yHGMjzS6HiPpJ3IwEeOo8qHx/H6wOKxLOSjK7JCKivnI+gMmq6mxZoaq1InI9gM/B8Nsn2OIbnJpFxApfF2eISCIAr7klEfVc7b+rUfnuPkRPiUHsCXFml0M0KOSvX4/3pk/H6yNH4r3p05G/fr3ZJfWZhLMTEX1sLCre3YfKf1WYXQ4RUV/x+ofeFqpaB+PzOh08tvgGp6UA1gFIEpHFAC6Ar4sF0ZDRkOtCyZoiRIywIemCVIhwwBui/PXrsXXRInhcLgCAq7AQWxctAgBkzJ5tZml9QkSQdGEKPE4Pyl8tgdVuRfQxMWaXRUR0sFRE4uCbaaUtNk71EY7qHKREZCyAU+D7B/ZPVd3eg2NXADgbQKmqTmhn+0kA1gPYbax6RVXvN7adCeCvAKwAnlDVP3TnMTmqM/lzVzcj9//2QCyCzNtyEBLJ7/CIAOC96dPhKiw8YL0tLQ2nfvSRCRX1D6/bi8JleXD96ETq/AxETogyuyQiChBmjOosInvgC7jtBV9V1REDWU+gYvClHhOREwDUAXimk+B7h6qe3Wa9FcD3AE4DkA/gKwBzVfW7rh6TwZdaeJu8yH90L5qKG5F5cw7C0yLMLolo0Hh95Eigvf/XRTBr166BL6gfeRs8yP97LpqKGpF+TRZsh9jNLomIAoCZ0xlR/+I1vkFIRJ425glrWY4zWnG7RVU3AujNxVWTAexS1Z9UtQnAGgBDv+8dDRhVRemLRWjMbUDKvDSGXqI2bKmpPVo/lFkirEj/VSZC4kJR+EQeGgsazC6JiIgGMQbf4DRRVataFlS1EsARffwYx4nIFhF5U0QONdalA8jz2yffWEfULZXv70Pt5hoknJWIyInRZpdDNOiMveMOWG22/dZZbTaMveMOkyrqX9bIEKRfmwVLhAUFj+WiqazJ7JKIiGiQYvANThbjAnoAgIjEo28HOvs3gGxVnQTgYQCvtjxUO/t22NdeRBaKyCYR2eR2u/uwPBqK6r6pxb43yhB5RDTiTk0wuxyiQSlj9mxMXLwYtrQ0QAS2tDRMXLw4IAa26khoXCjSr8sCFCj4ey7cVc1ml0RERIMQr/ENQiJyOYC7Aaw1Vl0I4H9V9ZkenCMHwIb2rvFtZ989AI4GMArAfap6hrH+LgBQ1Qe6Ogev8Q1ujUUNyPvrXoQlhiHjxmxYwvidHRHtryHPhfxHcxEaF4qMG7JhdVjNLomIhiCzrvEVEQuArd35bE29w0+PQcgIuOcDKDFu5/ck9HZFRFLEmFtGRCbD9z7bB99gVqNEZLiIhAG4GMBrffW4FJg8dW4UPpEPS7gFaQsyGHqJqF0RmTakLchAc1kTCpfnwdvIGUCIaOhQVS+ALSKSZXYtgYpzgAQhEQkHcDiAaPjeAxeICFqmHOrG8asBnARgmIjkA7gXQCgAqOpj8M0LfJ2IuAG4AFysvq4FbhG5AcDb8E1ntEJVv+3L50aBRd2KopUF8NS4kXFDNkJiQ80uiYgGMfsoB1IuT0PRygIUPZWPtKszISGc45uIhoxUAN+KyJcAWrs6quo55pUUONjVOQiJyFsAqgFsBuBpWa+qD5pWVBfY1Tn4qCpK1xaj5rMqJF+ahuijYswuiYiGiOovqlC6pgiRR0Qj5dI0iIXhl4i6x8zpjETkxPbWq+q/BrqWQMQW3+CUoapnml0EUWeqP6lEzWdViDs5gaGXiHokZkosvE4Pyl8rRZnNgsQLUmBcgUNENGgx4PYvXiwXnD4VkcPMLoKoI87v61G2rgSOQyOR8ItEs8shoiEobkYC4k5OQPWnVah4s8zscoiIuiQix4rIVyJSJyJNIuIRkRqz6woUbPENTtMAXCkiuwE0wjfNkKrqRHPLIgKayppQ9HQ+wpLC2UWRiA5KwtmJ8Dg9qHh3HyyOEMSdGG92SUREnXkEvsFf18I3I8rl8M2KQn2AwTc4zTS7AKL2eFweFD6RB4j4RnCO4HQkRNR7IoKkC1PgcXpQ/moJrHYroo/hpRNENHip6i4RsaqqB8BTIvKp2TUFCnZ1DkKquhdALIBZxi3WWEdkGvUqip8tQHN5E1KvTEfosDCzSyIaklatAnJyAIvF93PVKrMrMpdYBCmXpcE2yo6SNYWo+6bW7JKIiDriNKb8/I+I/ElEbgVgykBbgYjBNwiJyM0AVgFIMm7PiciN5lZFwa789VI4t9cjaU4K7CP5N56oN1atAhYuBPbuBVR9PxcuZPi1hFiQdlUGwtMjUPxMAVw/Os0uiYioPZfBl89ugG86o0wAc0ytKIBwOqMgJCJbARynqvXGsgPAZ4P5Gl9OZxTYar6sQsnqIsRMi0PSnBSzyyEasnJyfGG3rexsYM+ega5m8PHUuZH38N7WucHD0yPMLomIBhkzpzMyHt8GIEtVd5pVQ6Bii29wEvjN32vc5whCZArXbidKXyyGbZQdiecmm10O0ZCWm9uz9cHGGhmC9GuzYImwoOCxXDSVNZldEhFRKxGZBeA/AN4ylg8XkddMLSqAMPgGp6cAfCEi94nIfQA+B/CkuSVRMGqubEbRinyExIUg9YoMiJXfvxAdjKysnq0PRqFxoUi/NgtQoOCxXLirms0uiYioxX0AJgOoAgBV/Q+AHNOqCTAMvkFIVR8CMB9ABYBKAPNV9S+mFkVBx9voRdGTeVC3Iu3qTFgdHMGZ6GAtXgzY7fuvs9t96+lnYcnhSFuYCU+9BwWP58FT7+n6ICKi/udW1WqziwhUDL5BRERGisjxAKCq/1bVpar6VwCRInKIyeVREFGvomR1IRoLG5FyWTrCksPNLokoIMybByxb5rumV8T3c9ky33raX0SWDWkLMtBc1oTC5XnwNnrNLomIgpSI/ENEhgP4RkQuAWAVkVEi8jAATmfURxh8g8tfALQ3j4PL2EY0ICreKUfdlloMm5UEx/hIs8shCijz5vkGsvJ6fT8ZejtmH+VAyuVpaMh1oWhlPtTNAT+JyBQrAbwNYA+ACQAaATwPoBrAzaZVFWAYfINLjqpubbtSVTeB1w/QAKn9Tw0q3i5H1OQYxJ4Ub3Y5RIFn9yrg1RzgeYvv5+4gn8uoC5ETo5F0USqcO+pR/Hwh1MvwS0QDS1VfBHAEgEgAvwDwAoA18F2S+F8mlhZQQswugAZUZ/M22AasCgpaDfkNKHm+EBE5NiRdmAIRDmZF1Kd2rwK+XAh4jHlqnXt9ywAwnE2/HYmZEgtvvQflr5eizGZB4gX8+0REA64Zvrl7w+ELwPwWro8x+AaXr0TkV6q63H+liCwAsNmkmihIuGvdKHoyD1aHFanzM2AJYYcToj63ZdHPobeFx+lbz+DbqbiTE+Cp96Dy/X2wRoYgYWai2SURUZAQkTMBPATgNQBHqqqzi0OoFxh8g8stANaJyDz8HHSPBhAG4DyziqLA53V7UbQiHx6nBxk35iAkmn96iPqFs4MJeztaT/tJODsRnno3Kt4ph8VuRdyJvByDiAbEIgAXquq3ZhcSyPjpM4ioagmAqSIyA74L5wHgDVV938SyKMCpKkpfLEbDHhdSrkhHREZnPe6J6KDYs3zdm9tbT10SESRdmAqPy4vyV0tgtVsRfUyM2WURUYBT1elm1xAM2NcwCKnqB6r6sHFj6KV+VfVhBWq/qkb8GcMQdXi02eUQBbZJiwFrm4l8rXbfeuoWsQpSLk2DbZQdJWsKUfdNe5MhEBHRUMPgS0T9pv67OpS/XorISVGIP32Y2eUQBb7h84DJywB7NgDx/Zy8jNf39pAl1IK0qzIQnh6B4mcK4PqRl9sREQ11osoBw2jwczgcWl9fb3YZ1ANNJY3I+8sehCaEIuPGHFjC+T0bEQ0tnjo38h7eC0+NGxk3ZCM8nZdqEAU6EXGqqsPsOqjv8ZMoEfU5T70HhU/kQUIEqQsyGXqJaEiyRoYg/dosWCIsKHgsF01lTWaXREREvcQW3yAkIuEA5gDIgd8AZ6p6v1k1dYUtvkOHehQFj+ei4ScX0v8rC7bh9q4PIiIaxJpKGpH/8F5IuAWZN2UjJCbU7JKIqJ+wxTdwsRkmOK0HMBuAG76JsltuRAet7NUSuH5wIumXKQy9RBQQwpLDkbYwE556Dwoez4On3mN2SURE1ENs8Q1CIvKNqk7oes/Bgy2+Q0P1p5UoXVuM2JPikTg72exyiIj6lPOHehQ+nofwzAhfF2hexkEUcNjiG7j4Fzs4fSoih5ldBAUW5656lL5cDPs4B4bNSjK7HCKiPmcf5UDK5Wlo2OtC0cp8qJuNB0REQwWDb3CaBmCziOwUka0isk1EtppdFA1dzeVNKFpZgLDEMKRclg6xiNklERH1i8iJ0Ui6KBXOHfUofr4Q6mX4JSIaCkK63oUC0EyzC6DA4WnwoPDJfEAVqQsyYbVZzS6JiKhfxUyJhbfeg/LXS1FmtyBxTgpE+IUfEdFgxuAbhFR1r4hMAjDdWPWRqm7p7vEisgLA2QBK27tWWER+DWCesRgCYByARFWtEJE9AGoBeAC4VfXo3j8TMpt6FSXPFaKptBHp12QhLDHM7JKIiAZE3MkJ8NR7UPn+PlgdIUiYmWh2SURE1Al2dQ5CInIzgFUAkozbcyJyYw9OsRLAmR1tVNU/q+rhqno4gLsA/EtVK/x2mWFsZ+gd4vb9owz139Yh8bxk2EdzHAgiCi4JZyciekoMKt4pR+W/Kro+gIiGPBFZISKlIvKN37p4EXlXRH4wfsb5bbtLRHYZlxieYU7VBDD4BqsFAKao6j2qeg+AYwH8qrsHq+pGAN39H34ugNU9L5EGu5pN1aj85z5EHxeLmOPjuj6AiCjAiAiSLkyFY2IUyl8tQc2marNLIqL+txIHNgDdCeCfqjoKwD+NZYjIeAAXAzjUOOZvIsJrwkzC4BucBL6uxi08xrq+fRARO3z/yF/2W60A3hGRzSKysK8fkwZGw14XSl8ogu0QO5J4bRsRBTGxClIuTYNtlB0lqwtR922t2SURUT/qoAFoNoCnjftPAzjXb/0aVW1U1d0AdgGYPBB10oEYfIPTUwC+EJH7ROQ+AJ8DeLIfHmcWgE/adHM+XlWPhG+Arf8SkRM6OlhEForIJhHZ5Ha7+6E86g13VTMKV+TDGh2C1CvTIVaGXiIKbpZQC9KuykB4egSKny6A60en2SUR0cBKVtUiADB+tszrmA4gz2+/fGMdmYDBNwip6kMA5sP3bVUlgPmq+pd+eKiL0aabs6oWGj9LAaxDJ996qeoyVT1aVY8OCeE4bIOBt8mLwhX58DZ6kXZ1JqyR/L0QEQGAJcKK9IWZCIkLReETeWgsaDC7JCLqnZCWhhfjdjA9FNtrHeAcaCZh8A1CInKUqv5bVZeq6l9V9WsRmdXHjxED4EQA6/3WOUQkquU+gNMBfNP+GWiwUVWUrClCY34DUi5NQ3hquNklERENKtbIEKRfmwVLhAUFj+eiqazJ7JKIqOfcLQ0vxm1ZN44pEZFUADB+lhrr8wFk+u2XAaCwb8ul7mLwDU7LReSwlgURmQvgv7t7sIisBvAZgDEiki8iC0TkWhG51m+38wC8o6r1fuuSAXwsIlsAfAngDVV966CeCQ2Yyvf2oe7rGiSclYjICVFml0NENCiFxoUi/dosqBcoeCwX7upms0siov73GoArjPtX4OeGn9cAXCwi4SIyHMAo+D4DkwlEla3twUZERgB4Cb65dqcBuBzA2ao6aIejdDgcWl9f3/WO1C/qttag6KkCRB0VjeR5aRzMioioCw25LuT/LReh8aHI+K9sWB0cyJVoKBARp6p2OEej0QB0EoBhAEoA3AvgVQAvAsgCkAvgwpYxbkRkEYCrALgB3KKqb/Zn/dQxBt8gJSKj4ftHmgfgXFV1mVtR5xh8zdNY2IC8v+5BWEo4Mm7IhiWUHUWIiLrD+UM9Ch/PQ3hmhK8LdDj/fhINdl0FXxq6GHyDiIhsw/4X1CcBqAbQCACqOtGMurqDwdcc7lo38v5vD9SryLo1ByExoWaXREQ0pNRtrUHRygLYxziQtiATEsIeM0SDGYNv4GLwDSIikt3ZdlXdO1C19BSD78BTtyL/73vRmNeAjBuyEZFlM7skIqIhqfrzKpS+UITII6KRcmkaxMLwSzRYMfgGLs5FEkRagq2IhAOYAyAH+78H7jehLBqEVBWlLxWh4ScXUi5PZ+glIjoIMcfGwuv0oPz1UpTZrUick8yxEoiIBhiDb3BaD18X580wujkT+avaWImaL6oRd1oCoo6INrscIqIhL+7kBHjqPah8fx+sDisSZiaaXRIRUVBh8A1OGap6ptlF0OBUv6MO5etL4DgsEgln8oMZEVFfSTg7EZ56NyreKYfFbkXcifFml0REFDQ4vGBw+tR/Hl+iFk2ljSh+ugBhqeFImZfO69CIiPqQiCDpwlQ4DotC+aslqNk0aGcRJCIKOAy+wWkagM0islNEtorINhHZanZRZC6P04PCJ/IhVkHaggxOu9GPVq0CcnIAi8X3c9UqsysiooEiVkHKZWmwjbKjZHUh6r+tNbskIqKgwFGdg1BHoztzVOfgpR5F4fI8OHfVI+O6bNgOsZtdUsBatQpYuBBwOn9eZ7cDy5YB8+aZVxcRDSxvgwf5f8tFU3Ej0q/J4t9dokGCozoHLgbfICUicQBGAYhoWaeqG82rqHMMvv2rbF0JqjZWIOmiVMQcG2t2OQEtJwfY285XTNnZwJ49A10NEZnJXedG/sN74alxI+OGbISnR3R9EBH1KwbfwMW+jEFIRK4GsBHA2wD+x/h5n5k1kXmqP69C1cYKxJ4Qx9A7AHJzgblTV2H3X3Lgec6C3X/Jwdypq5Cba3ZlRDTQQiJDkH5tFiwRFhQ8noumsiazSyIiClgMvsHpZgDHANirqjMAHAGgzNySyAyun5wofakI9tEODDsn2exygsINs1Zh+dULkZO4FxZR5CTuxfKrF+KGWbzQlygYhcaFIv3aLKgXKHgsF+7qZrNLIiIKSAy+walBVRsAQETCVXUHgDEm10QDrLmiGUVP5SM0PgwpV6RDrBzBeSD87y8XwRHu3G+dI9yJ//3lIpMqIiKzhSWHI31hJjz1HhQ8ngdPvcfskoiIAg6Db3DKF5FYAK8CeFdE1gMoNLUiGlDeRi8Kn8yDuhVpV2fAareaXVLQiJT2+zR3tJ6IgkNElg1pV2WgubQJhU/kwdvoNbskIqKAwuAbhFT1PFWtUtX7APwOwJMAzjW1KBow6lUUrypAU1EjUq5IR1hSuNklBRd7Vs/WE1HQsI92IOXyNDTsdaFoZT7UzQFIiYj6CoNvkFPVf6nqa6rKETWCRMVbZajfVodhs5PhGBtpdjnBZ9JiwNpm2hKr3beeiIJe5MRoJP0yFc4d9Sh+vhDqZfglIuoLIWYXQANHRGoBtPwP2nJBpxr3VVWjTSmMBkzt1zWoeHcfoqfEIPaEOLPLCU7Djcl6tywCnLm+lt5Ji39eT0RBL+bYWHjqPdi3oRRldisS5yRDhOMwEBEdDM7jS0MC5/E9eA25LuQ/shfhGRHIuD4bEsIPUUREg1n5ayWo/KAC8acPQ8LMRLPLIQoKnMc3cLHFNwiJSASA6wFMg6/F9yMAj7WM9EyBx13djKIV+bBGWpE6P4Ohl4hoCEiYlQSP04OKd8phdVgRe0K82SUREQ1ZDL7B6RkAtQAeNpbnAngWwIWmVUT9xtvsReGKfHhcHmTelIOQKP6zJyIaCkQESRemwuP0omxdCSx2K6KPjjG7LCKiIYmfgIPTGFWd5Lf8gYhsMa0a6jeqitIXitCY24DU+ekIT48wuyQiIuoBsQpSLktD4fI8lKwuhNVmgePQKLPLIiIacjiqc3D6WkSObVkQkSkAPjGxHuonle/vQ+3mGiTMTETkRI5dRkQ0FFlCLUi7KgPh6REoeroArh+dZpdE1G9UFU3lTWiuaja7FAowHNwqCInIdgBjAOQaq7IAbAfghW9054lm1dYRDm7Vc3Xf1KJoRT4iD49GymVpHBGUiGiIc9e5kf/wXnhq3Mi4IZu9eCggqFfRVNQI109O4+aCp8aNuFMTMOwXSQNeDwe3ClwMvkFIRLI7266qeweqlu5i8O2ZxqJG5P11D8ISw5BxYzYsYezcQUQUCJorm5G/dA/Uo8i4MQdhiWFml0TUI163F425Da1Bt2G3C94GLwAgJDYEthF2RIywwz7GgbBhA//+ZvANXAy+NCQw+Hafp86NvL/sgbfJi6zbhiMkNtTskoiIqA81lTQi7+G9sIRbkHlTNkJi+HeeBi9PgwcNu12tQbcxtwHq9uWPsOQwRIyww2bcQuPNfy8z+AYuBt8gJSKTAEw3Fj9S1UE9uBWDb/eoR1HwWC4a9riQcUM2IrJtZpdERET9oCHXhfy/5SI0PhQZN2TDareaXRIRAMBd4/65NfcnJxoLG32TZ1qA8IyI1pBrG26DNXLwjbPL4Bu4GHyDkIjcDOBXAF4xVp0HYJmqPtzxUeZi8O2e0rVFqP60Csnz0jjlBRFRgHN+X4/CZXkIz4xA+rVZsITzshYaWKqK5vLm1pDr+smJ5nLfoFQSJojItrUG3Yhs25B4jzL4Bi4G3yAkIlsBHKeq9cayA8Bng3FQqxYMvl2r+rgCZS+XIO7kBAybNfCDQRAR0cCr21qDopUFsI9xIG1BJiSEAxlS/1GvorGwsTXkun5ywlPrAQBYHFbYhv8cdMMzIiDWofd+ZPANXIOvfwENBAHg8Vv2GOu6d7BIJoBnAKTANxL0MlX9a5t9BMBfAZwFwAngSlX9t7HtTGObFcATqvqH3j8VAnzf+petK4FjfCQSfpFodjlERDRAIidGI+mXXpS+UITi5wuRcmkaxDL0wgYNTt7mNgNR7fEbiCouBPbRjtbBqMKSwvjeo0GNwTc4PQXgCxFZB1/gnQ3gyR4c7wZwu6r+W0SiAGwWkXdV9Tu/fWYCGGXcpgD4O4ApImIF8CiA0wDkA/hKRF5rcyz1QFNZE4qezkdYUjiSL+MHHiKiYBNzbCw89R7s21CKMrsViXOSOYUd9YrHZQxEtdsJ14/GQFQeYyCqlHBEHhEN2yHGQFRx5g9ERdQTDL5BSFUfEpEPAUwzVs1X1a97cHwRgCLjfq0xL3A6AP/wOhvAM+rrS/+5iMSKSCqAHAC7VPUnABCRNca+DL694HF5UPRkHiCCtAUZsEZwcBMiomAUf0oCvPVuVH5QAavDioSZ7P1DXXNXN8P1088jLjcV/TwQVURmBGJOiPt5ICrHwMSG/PXrsWPJEriKimBLTcXYO+5AxuzZA/LYFNgYfIOXB74/bQpfd+VeEZEcAEcA+KLNpnQAeX7L+ca69tZP6e3jBzP1KoqfLUBTWRPSr8tCqAlz3RER0eCRMCsJHqcHFe+Uw+qwIvaEeLNLokHEfyCqlsGo2g5EFX/6MNgOsSMiy5yBqPLXr8fWRYvgcbkAAK7CQmxdtAgAGH7poDH4BiG/UZ1fhq+r83Mi0uNRnUUk0jjHLapa03ZzO4doJ+vbO/9CAAsBICyMoa6t8g2lcG6vR+IFKbCP5BgMRETBTkSQdGEqPE4vytaVwOKwIvoojvAfrNSraCxogOsnl28wqt0/D0RldVgRMcKGmON9Lbrh6YNjIKodS5a0ht4WHpcLO5YsYfClg8bgG5wWAJjiN6rzHwF8BqDbwVdEQuELvatU9ZV2dskHkOm3nAGgEEBYB+sPoKrLACwDfKM6d7e2YFDzZRWqPqhAzLQ4xB4fZ3Y5REQ0SIhVkHJZGgqX5aHk+UJYIyxwHBpldlk0AA4YiGq3C97GloGoQlsHorIdYkdoUtigvA7cVVTUo/VEPcHgG5wOdlRngW8wrO2q+lAHu70G4AbjGt4pAKpVtUhEygCMEpHhAAoAXAzgkl48h6Dl2uNE6YvFsI2yI/HcZLPLISKiQcYSakHqggwUPJqLoqcLkH5NFmyH2M0ui/qYx+UxphXyXaPbmOc3EFVqOKKOjkbE8KE1EJUtNRWuwgPbQ2ypqSZUQ4GGwTc4+Y/qDADnomejOh8P4DIA20TkP8a6uwFkAYCqPgbgH/BNZbQLvumM5hvb3CJyA4C34ZvOaIWqfnswTyaYNFc2o2hFPkLiQpB6Rcag6JZERESDjzXCirRrMpH/8F4UPpGHjBuyEZ4eYXZZdBA6H4jKhtgT4hAxwg7bcDusjqE52OXYO+7Y7xpfALDabBh7xx0mVkWBQnyD7lIwEJEzVPVt4/6R8I3qLAA2AhipqmvNrK8zDodD6+vrzS7DVN5GL/If3oPmfc3IvCUHYcnhZpdERESDXHNlM/KX7oF6FBk35iAskWNmDAWqiuayptag2/CTE837fh6IypZjR8QIm28O3WwbLGEDPxBVfzF7VGcRcaoqB08JQAy+QUREPPCF3EtVtaDNtn+r6pHmVNa1YA++6lUUP1OAuq21SLs6E47xkWaXREREQ0RTSSPyHt4LS7gFmTdlIyRmaHR7DSbqUTQWNuwXdD11/gNR2WEzgu5gGYgqUDH4Bi52dQ4uWwE8D9+8ure1aeHlX9BBrOKdctRtqcWwc5IYeomIqEfCksORvjAT+X/LRcHjvm7PVvvQ7AobKLxNXjTkutDQ0nV5jwvaMhBVfCjsYyNbg+5gHYiKaKhhi28QaWnVFZHRAFYB+AbAf6mqky2+g1ftlhoUryxA1DExSJ6byv/8iIioV5zf16NwWR7CMyOQfm1W7+dp3b0K2LIIcOYC9ixg0mJg+Ly+LTbAeJweuHY7W4NuQ56rdWjRsJRw32jLI2yIGGFHaGxwt8ivWgUsWgTk5gJZWcDixcC8AXx7scU3cLHFNwip6vcichyA/wfgaxG53OyaqH2NBQ0oeb4QETk2JP0yhaGXiIh6zT7agZTL01C0sgBFK/ORtiATEtLD/1d2rwK+XAh4nL5l517fMsDw68dd1WwMQuULuk3FxkBUVt9AVHEnJviu0R1uZ+u7n1WrgIULAafx9tq717cMDGz4pcDEFt8gIiJfq+oRbdadBGAFgERVHbQT/QVji6+71o28h3YDADJvHY6QaH5PRUREB6/680qUvlCMyCOikXJpGsTSg/D7ao4v7LZlzwbO3dNXJQ4pqorm0qb9gq67whiIKtwCW7YNEYcYA1FlBdZAVH0tJ8cXdtvKzgb27BmYGtjiG7j4STq4/E/bFar6oYgcBeAaE+qhDnjdXhStyIen3oOMm3IYeomIqM/EHBsHT70H+zaUocxhReL5yd3vUeTM7dn6AKQeRWNBQ2vQbdjtNxBVpG8gqtgT4mEbYUN4Ggei6oncXGDu1FX4318uQtawXOSWZ+HuFxdjzWds7qWDx0/TQURVX+1gfSWAPwxsNdQRVUXp2mI07HEh5Yp0RGRw3kUiIupb8acMg7feg8oPKmB1WJFwZmL3DrRnddDim9W3BQ4iLQNRuX5youFHF1x72xmIymjRDU3kQFQH44ZZq/DAuQvhCPf1dc5J3IvlVy/EsGEAwPBLB4ddnWlICKauzpUf7kP5+lLEnzGs+x9EiIiIekhVUfpCEWq+qEbiecmIPSG+64PaXuMLAFY7MHlZwFzj66lvGYjKaNHN9xuIKtUYiGq4L+iGBPlAVH2tblUOIuXAL1bqNBuR8/YMSA3s6hy42OJLNIjUb69D+WuliJwYhfjTh5ldDhERBTARQdKFqfA4PShbVwKLw4roo2I6P6gl3AbQqM7NVc1GyPUF3aaiRt8Gv4GobCNsiOBAVP0uUtrvMt/ReqKeYIsvDQnB0OLbVNKIvL/sQWhCKDJuzOn9NBNEREQ94G32onBZHlw/OZF2VQYchw7asS4PWutAVD8aQXe3a/+BqHKMQahG2DgQlRkGweBpbPENXAy+NCQEevD11HuQ95fd8DZ4kXnbcITGsesUERENHE+DBwWP5qKppBHp12bBNsLe4b5mz7PaE/sPROWbR9dT//NAVL6Qa+dAVIPFIOhKz+AbuBh8aUgI5OCrHkXB47lo+MmF9P/Kgm14xx82iIiI+ou7zo38pXvhqXUj44ZshKcfOLhi23lWAcBuB5YtGxzh19vkRcNel69Fd7cLDXuc0CbfZ93QhFAj5PqCLgeiGqR2rzK1Kz2Db+Bi8KUhIZCDb+nLxaj+uBLJc1MRPTnW7HKIiCiINVc2I3/pHqhHkXFTDsKGhe23fTDMs+qvZSAqX2uuEw15DYAX+w9EZQTdkBj2pqKudSf4isitAK4GoAC2AZgPwA7gBQA5APYA+KUxcwoNEgy+NCQEavCt/rQSpWuLEXtSPBJnJ5tdDhERkW/MiYf3whJuQeZN2fsFRosFaO+jowjg9fZ/bc2Vza0h1/WTC03FvoGoxCoIz4poDboRw22w2jgQFfVcV8FXRNIBfAxgvKq6RORFAP8AMB5Ahar+QUTuBBCnqr8dmKqpOziqM5FJnLvqUfpyMezjHBg2K8nscoiIiAAAYcnhSF+YifxH96Lg8Txk3JDdOppxVlb7Lb5Z/TCNr6qiqaTJb8RlJ9yVbgCAJdyCiOE2RB0ZDdsIO8KzImAJ5UBUNGBCANhEpBm+lt5CAHcBOMnY/jSADwEw+A4ibPGlISHQWnyby5uQ+5c9sDqsyLwlh99KExHRoOPcWY/C5XkIz4xA+rVZsIRb+vUaX/UoGvN/HojKtdsFb8tAVFHWn1tzR9gRnhYOsfD6XOp73ezqfDOAxQBcAN5R1XkiUqWqsX77VKpqXP9WSz3BFl+iAeZt8KBwRT6girSrMxl6iYhoULKPcSD5sjQUP12AopX5SFuQiXnzfGGzL0Z19jYaA1G1jLi81/XzQFTDQuE4NLI17IYOC+VAVDRQQkRkk9/yMlVd1rIgInEAZgMYDqAKwFoRuXRgS6TeYIsvDQmB0uKrXkXRU/mo/64O6ddkwT6agwYSEdHgVv15JUpfKEbkkdFImZfW65ZWT70brp9+DrqN+T8PRBWeFv7ziMvDORAVmacb1/heCOBMVV1gLF8O4FgApwA4SVWLRCQVwIeqOmZAiqZuYYsv0QDa92YZ6r+pQ+L5yQy9REQ0JMQcGwdPvQf7NpShzG5F4vnJ3Wp9ba5o9ps/14mmkiYAPw9EFXdygq/rcg4HoqIhJRfAsSJih6+r8ykANgGoB3AFgD8YP9ebViG1i8GXaIDUbK5G5Xv7EH1cLGKm8ZIPIiIaOuJOToCn3oOqDypgdViRcGbiftvV6xuI6ucRl51wVxkDUUUYA1EdFcOBqGjIU9UvROQlAP8G4AbwNYBlACIBvCgiC+ALxxeaVyW1h12daUgY6l2dG/a6kP/IXkRk25B+XRbEyuuUiIhoaFFVlL5QhJovqjHs3GTYcmw/D0T1kwte54EDUdkOsSMslQNR0dDRncGtaGhiiy9RP3NXNaNwRT6s0SFIvTKdoZeIiIYkEUHShanwOD0of7WkdX3osFBETohsvUaXA1ER0WDE4EvUj7xNXhSuyIe30YvMa7NhjeQ/OSIiGrrEKki5LB01X1TBGhkC2wg7QqL5fxsRDX78S0XUT1QVJWuK0JjfgNSrMhCeGmF2SURERAfNEmpB7LR4s8sgIuoRjixA1E8q39uHuq9rkHBWIiInRJldDhERERFR0GLwJeoHddtqse8fZYg6KhpxpySYXQ4RERERUVBj8CXqY42FDSh+rgDhWRFI+mUqB/ggIiIiIjIZgy/1mIhkisgHIrJdRL4VkZvb2WeeiGw1bp+KyCS/bXtEZJuI/EdENg1s9f3LXedG4RP5sNisSLsqA5Yw/hMjIiIiIjIbB7ei3nADuF1V/y0iUQA2i8i7qvqd3z67AZyoqpUiMhO+ib2n+G2foarlA1hzv1O3ouipfHjq3Mi4IRshMaFml0RERERERGCLL/WCqhap6r+N+7UAtgNIb7PPp6paaSx+DiBjYKscWKqK0peL0fCTC8kXpyIiy2Z2SUREREREZGDwpYMiIjkAjgDwRSe7LQDwpt+yAnhHRDaLyMJ+LK/3dq8CXs0Bnrf4fu5e1enu1R9VoubzKsSdloCoI2MGpEQiIiIiIuoednWmXhORSAAvA7hFVWs62GcGfMF3mt/q41W1UESSALwrIjtUdWM7xy4EsBAAwsLC+rz+Du1eBXy5EPA4fcvOvb5lABg+74Dd63fWoezVEjgOi0TCmYkDVycREREREXWLqKrZNdAQJCKhADYAeFtVH+pgn4kA1gGYqarfd7DPfQDqVHVJZ4/ncDi0vr7+4IrurldzfGG3LXs2cO6e/VY1lTYi7y97EBIbisybc2AJZycKIiIioqFKRJyq6jC7Dup7/JROPSa++XmeBLC9k9CbBeAVAJf5h14RcRgDYkFEHABOB/BN/1fdA87cbq33uDwofCIfYhGkXZ3B0EtERERENEixqzP1xvEALgOwTUT+Y6y7G0AWAKjqYwDuAZAA4G/GPLZuVT0aQDKAdca6EADPq+pbA1p9V+xZHbT4ZrXeVY+i+JkCNFc0IeO6bITGD2BXbCIiIiIi6hF2daYhYUC7Ore9xhcArHZg8rLWa3zLXi1B1b8qkHRRCmKOjRuYuoiIiIioX7Grc+Bi30yitobP84VcezYA8f30C73VX1Sh6l8ViD0hjqGXiIiIiGgIYIsvDQkD2uLbCddPTuT/bS/shziQtjATYhWzSyIiIiKiPsIW38DFFl+ibmquaEbRU/kIjQ9DyhXpDL1EREREREMEgy9RN3gbvSh8Mg/qVqRdnQGr3Wp2SURERERE1E0MvkRdUK+ieFUhmooakXJFOsKSws0uiYiIiIiIeoDBl6gdq1YBOTmAxQJkpXqxeq1g2OxkOMZGml0aERERERH1EIMvURurVgELFwJ79wKqQH6pFb97PxX/yOcIzkREREREQxFHdaYhYSBHdc7J8YXetrKzgT17BqQEIiIiIjIBR3UOXAy+NCQMZPC1WHwtvW2JAF7vgJRARERERCZg8A1c7OpM1EZWVs/WExERERHR4MbgS9TG4sWA3b7/Orvdt56IiIiIiIYeBl+iNubNA5Yt813TK+L7uWyZbz0REREREQ09vMaXhoSBvMaXiIiIiIITr/ENXGzxJSIiIiIiooDG4EtEREREREQBjcGXiIiIiIiIAhqDLxEREREREQU0Bl8iIiIiIiIKaAy+REREREREFNAYfImIiIiIiCigMfgSERERERFRQBNVNbsGoi6JiBeAy4SHDgHgNuFxKTjw/UX9ie8v6m98j1F/Muv9ZVNVNg4GIAZfok6IyCZVPdrsOigw8f1F/YnvL+pvfI9Rf+L7i/oav80gIiIiIiKigMbgS0RERERERAGNwZeoc8vMLoACGt9f1J/4/qL+xvcY9Se+v6hP8RpfIiIiIiIiCmhs8SUiIiIiIqKAxuBLQUVEMkXkAxHZLiLfisjNxvp4EXlXRH4wfsYZ6xOM/etE5JE25/pQRHaKyH+MW5IZz4kGjz5+f4WJyDIR+V5EdojIHDOeEw0effX+EpEov79b/xGRchH5i0lPiwaRPv4bNldEtonIVhF5S0SGmfGcaPDo4/fXRcZ761sR+ZMZz4eGHnZ1pqAiIqkAUlX13yISBWAzgHMBXAmgQlX/ICJ3AohT1d+KiAPAEQAmAJigqjf4netDAHeo6qYBfho0SPXx++t/AFhV9b9FxAIgXlXLB/gp0SDSl++vNufdDOBWVd04EM+DBq++eo+JSAiAQgDjVbXcCCZOVb1vwJ8UDRp9+P5KAPA1gKNUtUxEngbwjKr+c+CfFQ0lbPGloKKqRar6b+N+LYDtANIBzAbwtLHb0/D9IYaq1qvqxwAaBr5aGmr6+P11FYAHjP28DL3UH3+/RGQUgCQAH/Vf5TRU9OF7TIybQ0QEQDR8QZiCWB++v0YA+F5Vy4zl9wCwVxR1icGXgpaI5MD3TeIXAJJVtQjw/WGG74NgdzxldBX8nfGfOxGAg3t/iUiscff3IvJvEVkrIsn9WC4NMX309wsA5gJ4Qdn9i9o4mPeYqjYDuA7ANhgtvwCe7M96aWg5yL9huwCMFZEco3fBuQAy+69aChQMvhSURCQSwMsAblHVml6eZp6qHgZgunG7rK/qo6GtD95fIQAyAHyiqkcC+AzAkj4skYawPvr71eJiAKsPvioKJAf7HhORUPiC7xEA0gBsBXBXnxZJQ9bBvr9UtRK+99cL8PVW2QPA3Zc1UmBi8KWgY/yH/DKAVar6irG6xLj2pOUalNKuzqOqBcbPWgDPA5jcPxXTUNJH7699AJwA1hnLawEc2Q/l0hDTV3+/jH0nAQhR1c39UiwNSX30HjscAFT1R6M3wYsApvZPxTSU9OFnsNdVdYqqHgdgJ4Af+qtmChwMvhRUjO7ITwLYrqoP+W16DcAVxv0rAKzv4jwhLSNUGn/EzwbwTd9XTENJX72/jA+KrwM4yVh1CoDv+rRYGnL66v3lZy7Y2kt++vA9VgBgvIgkGsunwXc9JwWxvvwbJsZMGsYI0NcDeKJvq6VAxFGdKaiIyDT4usVsA+A1Vt8N3zUmLwLIApAL4EJVrTCO2QPfwBxhAKoAnA5gL4CNAEIBWOEbWOE2VfUM0FOhQaiv3l+q+p2IZAN4FkAsgDIA81U1d6CeCw0+ffn+Mrb9BOAsVd0xcM+CBrM+/ht2LYCbATTD93/mlaq6b8CeDA06ffz+Wg1gknGO+1V1zQA9DRrCGHyJiIiIiIgooLGrMxEREREREQU0Bl8iIiIiIiIKaAy+REREREREFNAYfImIiIiIiCigMfgSERERERFRQGPwJSIiGkLE52MRmem37pci8paZdREREQ1mnM6IiIhoiBGRCQDWAjgCvrnE/wPgTFX9sRfnsnIOciIiCnQMvkREREOQiPwJQD0Ah/EzG8BhAEIA3Keq60UkB8Czxj4AcIOqfioiJwG4F0ARgMNVdfzAVk9ERDSwGHyJiIiGIBFxAPg3gCYAGwB8q6rPiUgsgC/haw1WAF5VbRCRUQBWq+rRRvB9A8AEVd1tRv1EREQDKcTsAoiIiKjnVLVeRF4AUAfglwBmicgdxuYIAFkACgE8IiKHA/AAGO13ii8ZeomIKFgw+BIREQ1dXuMmAOao6k7/jSJyH4ASAP+/nTu2QRgGwjD6X0HNKIiBEBMwBTuwCxtQI3bIBEhUhCIpmACUy3ud7cbtJ1u3yzTQ8vV1/PzRHQHg70x1BoDluyY5VVUlSVXt5/1tkmEcx3eSQ6ZBWACwOsIXAJbvnGST5F5Vj3mdJJckx6q6Zfrm7JUXgFUy3AoAAIDWvPgCAADQmvAFAACgNeELAABAa8IXAACA1oQvAAAArQlfAAAAWhO+AAAAtCZ8AQAAaO0Dnbm6uejxaeYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,zoojan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,zoofeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,zoomar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Zooplankon Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Surface Zooplankon Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average surface mesozooplankton concentration (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f00aee0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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pl5kdcOqpp07uvN/e3k5GRsbso48+eq++9nvjjTcS/vSnP6X1tn758uWJF154YWFv6wGuvPLK/AkTJsza2Ww4JoKvFzo6Oga1/dKlSzO/8IUvNDz00EOZXjy+iIwNpcuWsfL662kuLwfnaC4vZ+X11yv8ioiIyKiXkJAQWLt2bUJDQ4MBPPnkk6k5OTnt/e23YsWKxL/85S89Bt/29na+9KUvNS1evLikp/WdTj311G1vvfXW6p2rfAwF39raWt8hhxwydcaMGXtPnTp1xsMPP5wOsHbt2tg99thjn7POOmviXnvttc9hhx02pfMHMWfOnGnLly9PBKioqIjOz8/ft3OfAw44YNqMGTP2njFjxt4vvvhiEsCzzz6bcvDBB0895ZRTJk+bNm2fq666Ku+mm24a31nDlVdemf8///M/43uqbcWKFcl/+MMfNjz55JMZAI8++mjql7/85T06t3n22WdTjjnmmL0AnnjiidT99ttv+owZM/Y++eST96itrfUB5Ofn73vttdfmHnDAAdPuv//+jNtuuy1r5syZe0+bNm3GiSeeuGd9fb0P4MMPP4ybPXv29JkzZ+793e9+N6/rtx4/+clPcmbOnLn31KlTZ3zve9/LG+Ifg4jsojW33oq/ubnbMn9zM2tuvdWjikREBsY5x6aGTSzfuJwH33+QZz9+lpWbVrKtZRvBwWxFZDTZsGRJ5guHHLLvM3vtdcALhxyy74YlS4akge7YY4+tfeyxx9IBHnnkkcx58+ZVd66rq6vzff3rX580c+bMvffee+8ZDz/8cHpLS4vdcsstec8880zG9OnTZ9x3330ZV199dd7ZZ5898bDDDpty+umnT3722WdTOluNa2trfWecccakqVOnzpg6deqMxYsXp4cet3HixIn9huzejJl5fBMTEwN/+ctf1mVmZgYqKiqiDz744OnnnHPONoDi4uL4hx9++LNDDz1045e//OU9HnzwwYzLL7+8urdj5eXldfzzn//8ODEx0a1atSru7LPP3uODDz5YDbBy5cqk995778Pp06e3rV27Nva0007b8yc/+clmv9/PU089lfHOO+/s8C3DkiVL0o866qjaWbNmtaanp/tfe+21xNNOO63uqquumlhXV+dLTU0NPPLIIxlnnHFGdUVFRfT//u//5i5fvvzj1NTUwPXXXz/hpptuyrn11lsrAOLj4wPvvvvuWoDKysqoa665pgrgO9/5Tt4dd9yRdf3112++4oorCi+//PLNl1xySfUvf/nL7M46nnjiidR169bFr1y5crVzjuOOO26vv/3tb8knn3xyw5D+MERkpzVXVAxquYjISGvpaOGTrZ+wduta1latDV6Hbte21va4T0psCkVpRTtcClMLKUorIj81n9io2BF+JiK7rw1LlmR+ePPNEwOtrT6A1s2bYz+8+eaJAJPOPbfXnDQQ5513XvWNN96Ye+aZZ25bvXp14oIFC7a+8cYbyQDXXXdd7tFHH1332GOPbaiqqoo68MAD9/7a175W9+Mf/7h8xYoVSQ8++GAxwNVXX52wcuXKxLfeemtNcnKye/bZZ1M6j/+jH/0oNzU11f/xxx9/BLBly5aoXam304CD77eWfavwg80fJA7Fg3aaOX5m0/1z7++zSbtTIBCw7373uwVvvvlmss/nY/PmzbGlpaXRAPn5+a2HHnpoM8D+++/ftGHDhri+jtXW1mYLFiyY+NFHHyX4fD42bty4fftZs2Y1Tp8+vQ1g2rRpbenp6R2vv/56QkVFRcw+++zTNGHChB1GYnv00Uczr7rqqs0A8+bNq37ooYcyDz/88KajjjqqbunSpWnz58+v+cc//pF21113lT733HMpn376afycOXOmA7S3t9sBBxywPZief/75NZ2333333YQbbrghv76+PqqxsTHqyCOPrAV47733kl944YV1ABdddNHWn/70pwUAzz33XOry5ctTZ8yYMQOgqanJt2bNmngFX5HRIyE3N9jNuYflIiIjxTlHWX3Z58G2S8DduG0jjs9bcAtSC5g2bhrn7nsu07KmMW3cNCZnTKamuYbi2mJK6koori3efllRvoItTVu6PZ5h5Kbkfh6KU8MCcloh4xLGYWYj/VKIRKSP77orvzP0dgq0tvo+vuuu/F0NvgcffHBzaWlp3H333Zd53HHHdfs27JVXXkl9/vnn0++4444JAK2trbZu3boev/U66aSTtiUnJ+/QXWT58uWpS5cu/azzfnZ29q6MhL3dmGnxvffeezO3bt0avWrVqtVxcXEuPz9/3+bmZh9AbGzs9hcsKirKdS6Pjo52fn/wdWpqatr+l/Tmm2/OGT9+fPuf//zn9YFAgISEhAM61yUmJga6Pu78+fOrfve732Vt3rw5Zv78+VvD66qsrIx68803Uz/++OOEK664Ar/fb2bmfvvb35aeddZZ1Xfffff4rKws/6xZs5oyMjICzjkOP/zwumeeeWZ9T88zJSVl++MvXLhw8uOPP77ukEMOab7jjjvGvfrqqyk97dPJOcd3v/vdiu9///tV/bycIuKR6ddey8rrr+/W3TkqIYHp117rYVUiEqka2hr4eOvHO7Tcfrz1YxrbG7dvlxSTxLSsaRxScAgXzr5we8CdOm4qSbFJvR7/4IKDe1ze1N5EaV1pt0DcGZL/U/kfnl77NC0dLd32SYhO6LHVuPNSkFpAfLTGEBUZiNYtW3oMm70tH6yTTjpp24033lj4wgsvrN28efP2TOmc4/HHH183e/bs1q7bv/baazv8IUlKSgqEL+s8xnB8CTbg4DvQltnhUltbG5WVldUeFxfnnnnmmZTy8vJ+f2iFhYWtb7/9dtLRRx/dtGTJkoyuxyooKGiLiorirrvuGtcZjnty3nnnbbv55pvzOzo6bN68eZ+Fr3/ooYcyTj/99K1//OMfN3YuO+igg6a98MILyV/5ylfqL7/88kn33Xdf1te//vVqgKOOOqrxmmuuKfrggw/iZs6c2VpfX+9bv359zKxZs1rDj93U1OQrKipqb21ttaVLl2bm5ua2A+y3334Nixcvzrj44otr7r///u199U8++eS6n/70p3kLFy6sTktLC6xfvz4mNjbW5efna6QskVGiYO5cIHiub3NFBQm5uUy/9trty0VEBssf8FNcW9xj1+Sy+rLt2xnGpPRJTMuaxpcmfolp46ZtD7h5KXlD+kEzMSaRqeOmMnXc1B7XO+eoaqraIRgX1wWv//rJX6lo2PEUkPFJ43ttNS5KKyI7KRufjZkhbESGTVx2dlvr5s075KW47Oy2oTj+ZZddVpWWluafM2dOc9duykcffXTdbbfdlrN48eJin8/H66+/nnDYYYc1p6am+hsaGgb0y3nUUUfV3X777ePvvz+YP7ds2RI1FK2+o77Ft729ndjYWHfRRRdVn3zyyXvNnDlz73322adp8uTJLf3t+6Mf/WjTmWeeucfSpUvHHXHEEXWdy7/73e9unjdv3p5PPfVUxuGHH16fkJDQ47cNAPHx8e7QQw+tS09P90dH7/hyPfbYY+N+8IMfdPvLPHfu3JqHHnoo86STTmo49thjax9//PFxjz766AYInl987733bjjrrLP2aGtrM4Abb7yxrKfg+6Mf/ah8zpw5e+fn57ftvffeTQ0NDVEAd955Z8m55547+Y477phwwgknbEtOTvYDnH766XUffvhh/EEHHTQdgq3XS5YsWa/gKzK6FMydq6ArIoNW21LbLdyuqVrD2q1r+WTrJ7T6P/8YkR6fzrRx0zh2j2OD4TYUcPfK3GvUtJiaGdlJ2WQnZXNA3gE9btPa0UpZfdmO4bi2mNVbVvP8uue7tVoDxEXFUZBa0GurcWFqYZ8t2CKRYuoVV5R1PccXwBcXF5h6xRVlfe03UHvuuWf7T37yk83hy3/+85+XL1y4sGj69OkznHNWUFDQ+vLLL687+eST62+99dbc6dOnz7jmmmv6HNjklltuqZg/f37RlClT9vH5fO66664rv+CCC7ZdeumlBU8++WRmS0uLLycnZ9a5555bdfvtt+94/lgvrK9R+N5///0Ns2fP9rTb7L/+9a+EhQsXTlq1atVOD129K/x+P/vss8+Mxx577NN99913h3Dqhfr6el9SUlLA5/OxaNGijD/96U+Zf//73z8dimO///77WbNnz540FMcaSklJSa6xsbH/DUVERMawjkAH62vW99h6u6lx0/btoiyKPTP37BZsO6+zE7N3i3NlnXPUtNRQUlvSY6txcW0x5fXlBFz39o1xCeO2n1fcU6vxhOQJRPmGZCwdGYPMrMk5Nyq/HRlsNtuwZEnmx3fdld+6ZUtsXHZ229Qrrijb1fN7R7u+ssyobvH95S9/mX3vvfeO/3//7/950s363XffjZ87d+6Uk08+uWa0hF6A119/PfGqq64qcs6RmprqX7x48Qava+pkZicBvwaigN85537ewzZHAb8CYoAq59yRI1iiiIiI56qaqnocWOrT6k9pD3w+W0dWYhbTxk3jq1O/2i3g7pGxBzFRMR4+A++ZGZkJmWQmZDJ7wuwet2n3t1NeX97jIFzra9bz6oZXdxipOtoX3a3VuHNk6q6X1LjUkXiKIrtk0rnnVkd60B2MUd/iKyNrV1p8zSwK+Bg4HigF3gHOds591GWbdOAN4CTnXLGZjXfO7dBNIpxafEVEZKxp7Wjl05pPd2i5Xbt1LdXNn38WjY2KZa/MvXpsvc1MGJJpN6UPtS213UJxSW1Jt1bj0rpSOgLdzxpLi0vrdeqmorQi8lLydvsvJsaqSGrx3R2N2RZfGXPmAOucc58BmNlSYC7wUZdtzgGecM4VAwwk9IqIiIxWzjkqGyp77Jq8ftv6bt1sc5NzmZY1ja/P+Hq3gDspfZK61nooLT6NtPg0Zo6f2eN6f8BPZUNljyNUF9cW82bpm2xt7j7xh8985KXk7TAQV2Ha5+E4Iz5jt+iSLjJaKPjKUMoHunZLLwXC5zmYCsSY2StACvBr59yDI1OeiIjIzmlqb+KTrZ/sEHA/3voxda3bx88kITqBqeOmckDeAZyz7znbA+7UcVPVPXaMivJFkZ+aT35qPocUHtLjNo1tjTt0pe68vFP2Dk+sfoI2f/fBdJNikvochKsgtYC46LiReIoiuwUFXxlKPX1tGd6XPho4ADgWSAD+ZWZvOuc+3uFgZguBhQCxsUMy5ZiIiEivAi5AWV3Z5yMmdwm4xbXF3bYtSiti2rhpnD/r/G5dkwtSCzSdzm4oKTaJ6VnTmZ41vcf1ARdgS+OWXqdveq/yPTY37tgJbkLyhF6nbypMK9xtBjITGQoKvjKUSoHCLvcLgPAhxksJDmjVCDSa2XJgNsFzg7txzi0CFkHwHN9hqVhERHY79a31fLz14x5bb5vam7ZvlxKbwrSsaRxRdES3rslTxk0hMSbRw2cgY43PfOQk55CTnMNB+Qf1uE1LRwuldaU9thqv2rSKv3z8F5o7mrvtEx8d3+PgW11bjhNiEkbiKYqMeqM++EZFRR0wZcqU7b/ly5YtWzdt2rQeJ16eM2fOtFtvvbXkS1/6UlNP673Q3t7O+PHjZ59zzjlVd99995DMmzWKvQNMMbPJQBlwFsFzertaBtxlZtFALMGu0P83olWKiEjE8wf8bKzd2OPIyeX1n38n6zMfk9MnMy1rGkdPOrpbwJ2QPEGtaTJi4qPj2StzL/bK3KvH9c45tjZv/XwArrBW4+c/fZ6K+gpcWGe7rMSsXluNi9KKyEnOUS8FGTAzO2Du3LnVTz311Hr4POvst99+jS+//PK63vZ74403EkpKSmLPPPPM2p7WL1++PPH+++8ft3jx4h5n86mvr/edcsope2zcuDEuKiqKE044YdtvfvObQWWrUR984+LiAmvWrPmo/y0Hpr29nZiYXRtlr6Ojg+jogb10TzzxRNrkyZNbn3766Yw777yzzOfbtT8sQ1H/cHHOdZjZFcDzBKczut8596GZXRpaf49zbrWZPQesBAIEpzz6wLuqRURkLKtprulxYKl11eto9X8+E2FGfAbTsqZx/B7Hdwu3e2XupfMoZUwwM7ISs8hKzOILuV/ocZs2fxtldWU9DsL1ydZPeOmzl2hoa+i2T4wvptv0TT21GqfEpYzEU5QxICEhIbB27dqEhoYGS05Odk8++WRqTk5Oe3/7rVixInHFihVJPQXf9vZ2vvSlLzX113h5zTXXbDrllFPqW1pa7LDDDpv66KOPpn7jG9+o62ufrkZ98O3JP//5z8Srr766sKmpyZeRkdGxZMmSDRMnTmwHWLx48birrrqqqKGhIWrRokXrjz766Karr746r6KiIqa4uDg2MzOz4/jjj69bsWJF0oMPPlgMcPTRR+91zTXXbPrqV79af+655xa9//77SS0tLb5TTjml5v/+7//KAfLz8/c9++yzq15++eXU4447rvaZZ57J+Oijj1YDrFq1Ku6ss87a48MPP1wdXusjjzySefnll2+67777sv/xj38kHX300Y1FRUX7vv/++x9lZWX5AYqKima+/vrra6Kiopg/f/7EsrKyWIDbb7+9+IQTTmgMr//WW28tO+eccyY3Nzf7AH79618XH3/88Y1+v58LLrig6M0330wpLCxsDQQCXHjhhVvnz59f09drNpScc38F/hq27J6w+/8P+H9D/dgiIhKZ2v3tfFbzWY8Bd0vTlu3bRfui2TNjT6ZlTePLU77cLeBmJWap9VYiXmxULJMzJjM5Y3KP651z1LbW9tiduqSuhFc3vkpZXRl+5++2X0Z8xuejUvfQapybkku0b0zGioh2zz1k/uxn5FdWEjthAm033EDZpZeyy/P6HnvssbWPPfZY+vz582seeeSRzHnz5lW/8cYbyQB1dXW+BQsWFK1evTrB7/fb9ddfX37GGWfU3nLLLXktLS2+6dOnJ19zzTUVq1evTuiaby655JKq2267Lefll19eV1tb61uwYEHRypUrEwGuu+668gsvvHDbKaecUg8QHx/vZs2a1VRSUjKoQYBG/Tu0tbXVN3369BkAhYWFrc8+++xn3/nOd4r+8pe/rMvLy+u47777Mq699tr8xx57bANAU1OT77333lvzt7/9LXnhwoWTP/nkkw8BVq5cmfjWW2+tSU5Odnfccce43h7v9ttvL8vJyfF3dHRw6KGHTnvrrbcSDj744GaA+Pj4wLvvvrsW4JVXXkl94403Eg499NDme++9N+ucc87ZGn6shoYGe+ONN1Ieeuihjdu2bYt6+OGHM4877rjGE044YduSJUvSr7rqqq3/+Mc/kgoKCtoKCws7TjnllMlXX331phNPPLHhk08+iT3xxBOnfPbZZzvUX19f7/vnP//5cWJiolu1alXc2WefvccHH3yw+sEHH8woKSmJXbt27YdlZWXRM2fOnHnhhRdubW1ttb5eMxEZXs45mtqbqGqq2n7Z2ryVpvYmkmOT+7zog4TsLpxzbGna0mPX5M9qPus2j+r4pPFMGzeNudPmdhtYanL6ZM2dKtIHMyM9Pp30+HRm5czqcZuOQAcV9RW9DsT1evHr1LTUdNsnyoIjX/c0p3HnJS0uTV8+jaB77iHze99jYksLPoCKCmK/9z0mAuxq+D3vvPOqb7zxxtwzzzxz2+rVqxMXLFiwtTP4XnfddblHH3103WOPPbahqqoq6sADD9z7a1/7Wt2Pf/zj8q4Nj1dffXVC13zz7LPPbu9W8KMf/Sg3NTXV//HHH38EsGXLlm7zvVVVVUW9+OKL6d///vc3DabuAX+i+taaNYUfNDYO6UgOM5OSmu6fPr3Hftydwrs6v/POO/GffPJJwjHHHDMVIBAIkJ2dvb3l8pxzzqkGOPnkkxsaGhp8VVVVUQAnnXTStuTk5H4HSHrggQcyFy9enNXR0WFbtmyJef/99+M7g+/555+//bf8wgsvrLrvvvuy5syZU7Js2bKMd955Z4fW3kcffTT9i1/8Yn1KSkrgm9/8Zs1+++2X19HRUXLOOedU/+xnP8u76qqrti5ZsiRz3rx51QCvv/566ieffLJ9BIKGhoaompoaX3j9bW1ttmDBgokfffRRgs/nY+PGjXEA//znP5NPP/30mqioKIqKijq++MUv1gOsXLkyrq/XTEQGp6WjpVuI3R5mm7YGbzfvuK6lo2WnHis+Or7PYJwSmzLo9QoG4qWWjhbWVa/boeV27da1bGvZtn27uKg4poybwr7j9+WMvc/oFnDT49M9q18k0kX7oilMK6QwrZDDOKzHbepb63udvulfJf/isbrHaA90/6iZEpvSYzfqztv5qfnERmkWj6Hys5+R3xl6O7W04PvZz8jf1eB78MEHN5eWlsbdd999mccdd1y3rsuvvPJK6vPPP59+xx13TABobW21devW9fiD7S2fLV++PHXp0qWfdd7Pzs7e3gWhvb2d008/fY+FCxdumjFjRo/jPvVmzDUlOOdsr732av7Pf/6zpqf14d8kdd5PSkraPoN8dHS0CwQ+n1C+tbXVB7BmzZrYu+66K+fdd99dnZ2d7Z83b96klpaW7W+YlJSU7TtdcMEFNb/4xS/yli5dWr/vvvs2TZgwoXufEGDp0qWZ7777bnJ+fv6+ALW1tVHPPvtsyte+9rX6BQsWxJWXl0c/99xz6TfffHN56LmxYsWK1T29AbrWf/PNN+eMHz++/c9//vP6QCBAQkLCAZ3778xrJrI7a/O3fR5Yw4Nsc8/LG9sbez1eRnzG9nOwClML2W/CfmQlZG1f1vWSGJNIY3sjDW0N3S71rfU7LGto775+U8OmbuvDR/rsS2xU7C4F5x22iUvRhxXpxjlHRUNFj623G7ZtIOA+/x+cn5LPtKxpnD3z7G5dk4vSiojyRfXxKCLilZS4FGZkz2BG9owe1wdcgE0Nm3ptNX6n/B2qmqq67WMYuSm524Pwmfucyel7nz4STyciVVbS4z/m3pYP1kknnbTtxhtvLHzhhRfWbt68eXumdM7x+OOPr5s9e3Zr1+1fe+21pPBjdM03XTnneu0dcM4550zaY489Wm644YYd5//qx4CDb38tsyNl1qxZLdXV1dEvvfRS0nHHHdfY2tpqq1atijvwwANbAB555JGMU045pf75559PTklJ8Y8bN26HQLrnnnu23XfffYl+v5/169fHrFy5MgmgpqYmKiEhIZCZmekvKSmJfuWVV9KOPPLI+p7qSExMdEceeWTt1VdfXXTXXXdtCF9fXV3tW7FiRXJZWdnKhIQEB/DrX/963B//+MfMU089tf7kk0/edvnllxfutddezZ2h+fDDD6/7xS9+Mf6mm27aBMHRzw499NAdPs3W1tZGFRQUtEVFRXHXXXeN8/uDT/GII45oeOihh8ZdccUVW8vLy6PfeuutlLPPPru6v9dMJFJ0BDqobq7uMaz2FmbrWnsfEyE1LnV7SM1JzmGf8fuQlZDFuMRxPQbZzIRMz7om+wP+7SG6x+AcHq7bdtymqqmq2/qu07r0J8YX02cwTo7pOzj3tDwuKk7d4ka5pvam4LRAYa23H2/9mPq2z/99JsYkMm3cNObkz+G8WedtD7hTx00lOTbZw2cgIsPBZz5yU3LJTcnl4IKDe9ymqb1p++jU4a3H71W8x5y8OSNcdWSZMIG2ioodQ+6ECQyqlbQ3l112WVVaWpp/zpw5zV27KR999NF1t912W87ixYuLfT4fr7/+esJhhx3WnJqa6m9oaBjQKL9HHXVU3e233z7+/vvvL4FgV+fs7Gz/d77znby6urqopUuXbtiZmsdci298fLxbunTpp9/5zneK6uvro/x+v1122WWbOkNcRkaGf//995/eObhVT8c4/vjjG+6+++7WadOm7TNt2rTmGTNmNAEccsghzTNnzmyaMmXKPkVFRa0HHHBAQ0/7dzr//POr//a3v2WcfvrpO3xyfvjhhzMOPfTQ+s7QC3DWWWdt++lPf1rQ3NxcfO6551YfeeSRe99xxx0bOtcvWrSo5KKLLiqaOnXqDL/fbwcffHD9oYceWhx+7O9+97ub582bt+dTTz2Vcfjhh9cnJCQEINgK/dJLL6VMnTp1n8mTJ7fMnj27MT093d/fayYyGgVcgJrmmt5DbPOOXYzDzznqKikmqVtInZI5pdv9cQndw+y4xHFjqhUzyhdFalwqqXGpMESDb/oDfpramwYcnHtaX1JXssO6AT8ni+ozGHeG6V7X99BqHR8drzA9SAEXoKS2pMeBpUrqPv9O3DCK0oqYljWNCwsv3B5up2dNJz8lX6+7iHSTGJMY7OGRNc3rUiLSDTdQ1vUcX4D4eAI33MCQTK+65557tv/kJz/ZodX15z//efnChQuLpk+fPsM5ZwUFBa0vv/zyupNPPrn+1ltvzZ0+ffqMa665pqKvY99yyy0V8+fPL5oyZco+Pp/PXXfddeWHH35445133pk7efLkln322WcGwMKFCzdfffXVVX0dqyvrrXsswPvvv79h9uzZAz7Y7uaGG27Iqa2tjfr1r39d3v/WI6O2ttaXlpYWqKysjDrooIP2fv3119cUFRV19L9n0Pvvv581e/bsScNY4k5JSkpyjY29dy+V0a1zFMm+WmLDW2Wrm6u7dYfsKi4qjuyk7O4trj10J+5smR2XMI6EmIQejyUjK+ACNLc3Dyw8d225bu97ffi8lb3xmW/nunP3sU1iTGJEhLq61roeuyZ/svWTbl3pU+NSu3VJ7rw9JXOKfs9EZMwzsybn3A7dckeDwWaz4RrVeTTrK8uMuRbf0eL444/fc+PGjXGvvvrqx17X0tXxxx8/pa6uLqq9vd2+//3vVwwm9IoMhHOO+rb67oM59dEa27ld+NQInWJ8Md3C6qycWT12I+7aMhspQWN35DMfSbFJJMUmkUPOkBzTOUdzR3P/4bmH86Y711c2VO7QYt3bFy/hDNul4NxTq3ViTCI+27V533vSEehgw7YNPQbcyobK7dtFWRSTMyYzbdw0jpt8XLeBpXKScvT7JyIyBlx6KdWRHnQHQ8F3J7344oufel1DT95+++21XtcgY0dv0+z01yIbPlJjpyiL6tbSOj1req8DO3VekmOT9SFadomZkRiTSGJMIuOTxg/JMZ1ztPpb+z1fuq9W66qmKtZvW98thPf2BVBPkmKS+j4POqb34Jwcm4xhwdGTu3RN/rTmU9r8n5/eNS5hHNOypnHyXid3a8XdM3PPMdXVX0REpD8KviIRZCin2TGs2yBOe2TswZz8OX2G2NS41GFppRIZaWZGfHQ88dHxZCdlD8kxnXO0+dt2+nzphrYGqpurKa4t7ra+a5DtSYwvhr0y92Ja1jS+Nu1r3QLuuMRep7UXERGJKAq+IqPUcE+zs/+E/XcY0KnrJT0+XVOJiAwhMyMuOo646LghDZw9hemGtgba/e3smbknk9IneTbauIiIyGih/4QivXivvp6mQICM6GjSQ5cEn2+nuuWO1DQ7XbsZj5ZpdkRkeMVGxZKZkElmQqbXpYiIiIxa+iQs0osff/YZz9d0nx4n1oz06GhSooxkc8TRQaxrJcrfjHU04m+vpaOthtbWrTQ1b6GxqYLahnLqmsqgowF6OL+vv2l2wqfaGWvT7IiIiIiIeG3UB18zO2Du3LnVTz311HqA9vZ2xo8fP3u//fZrfPnll9ft6vETExP3b2pqem8g2x577LF7bt26NeY///nPml19XBn9Dmp5FxrXU9XeSk17O3X+AI3O2Ew0m6OSIDq5yyUFosdDdF7wtyoRyNjxmHEESIky0qOjyIiOJSs2nqzYuO0tyl1blztvZ8TEhMJ2FD4NAiUiIiIiHtnZbPbGG28klJSUxJ555pm1Pa1fvnx54v333z9u8eLFJT2tBzjiiCOmbN68Ocbv99ucOXPqH3zwweLo6IHH2VEffBMSEgJr165NaGhosOTkZPfkk0+m5uTk9DykbC/a29uJiYnZpTqqqqqiPvzww6TExET/mjVrYqdPn973aCL96OjoYDA/qJFmZklAi3ODGII0wqwp/hsri18nKzGLid1aYFPJ6qk7cXwmRMWzraNj+6Wmn9sV7R181NTMto4Oav19v9Q+IK2HYLzD7VBQDl++s920RURERERg57PZihUrElesWJHUU/Btb2/nS1/6UtOXvvSlpr6OsWzZsk8zMzMDgUCAk08+ec/7778/Y+HChTV97dPV6E1eXRx77LG1jz32WPr8+fNrHnnkkcx58+ZVv/HGG8kAL7/8cuLVV19d1NLS4ouPjw8sXrx4/ezZs1vvuOOOcX/729/SWltbfU1NTb7nn39+3YIFC4pWrlyZCHDdddeVX3jhhdsArrzyyvwXXnghLT4+PvDss8+uKyws3GHu24ceeijjuOOO25aTk9P+wAMPZN5yyy2VX/nKV/Y4//zzt3b+AOfNmzfplFNO2fbNb35z27e//e2C119/PaWtrc0uvvjizd///vernn322ZSbbropd/z48e0fffRR4qeffvrhcccdt2dFRUVsa2ur79JLL9107bXXVgH83//9X9avf/3rCePHj2/fY489WmJjY92DDz5YXF5eHj1//vyJZWVlsQC333578QknnND7iEYD5Jyjqqoqc+vWrePNbDPQCsSZ2Rbgr8Ai59wnu/o4Y8ljX39sp/ZLjo6mYCf28ztH3UBCc3v79ttrmpq2324K9D3naGc37YEG5a6306OjifFptGYREYHSZctYc+utNFdUkJCby/Rrr6Vg7lyvyxKRcJ/ck8mqn+XTUhlL/IQ29r2hjCmX7vK8vn1ls7q6Ot+CBQuKVq9eneD3++36668vP+OMM2pvueWWvJaWFt/06dOTr7nmmorVq1cnVFRUxBQXF8dmZmZ2XHLJJVW33XZbzssvv7yutrbW11Nuy8zMDAC0t7dbe3u7DbZBZ0wE3/POO6/6xhtvzD3zzDO3rV69OnHBggVbO1/c2bNnt7z99ttrYmJieOqpp1J+8IMfFDz//POfAvz73/9OXrly5Yc5OTn+yy67LD81NdX/8ccffwSwZcuWKIDm5mbfIYcc0nDnnXeWXXrppQV33nln9i9/+cuK8Boee+yxzBtuuKE8Ly+v/YwzztjzlltuqTzzzDOr//SnP2WceeaZtS0tLfb666+nPvDAAxt/9atfZaWlpfk/+OCD1c3NzXbQQQdNP+WUU+oAVq5cmfTee+992NlivGTJkg05OTn+hoYG23///Wd885vfrGlpafHdeuutuf/+978/Sk9PDxx66KFT99lnn2aASy65pPDqq6/edOKJJzZ88sknsSeeeOKUzz777MNdfY1Xr149LSUlpS41NXUbUOCcCwCYWSZwNPBzM3vSOffwrj6W9CzKjIyYGDJ2sndCayBAbT9Buevy6o4OPmtp2b68w7k+j5/k8w04KIcHa3XTFhGJDKXLlrHy+uvxNzcD0FxezsrrrwdQ+BUZTT65J5N3vzeRQEuw5aKlIpZ3vzcRYFfDb1/Z7Lrrrss9+uij6x577LENVVVVUQceeODeX/va1+p+/OMfl69YsSLpwQcfLAa4+uqrE1auXJn41ltvrUlOTnbPPvtsSufxf/SjH+X2lNsADj/88CkrV65MOvLII2vnz58/4NZeGETw3fRIeWFrZWviYA7en7gJcU05Z+f12o+708EHH9xcWload99992Ued9xx3ZrHq6uro84888zJGzZsiDcz197evv3T9RFHHFGXk5PjB1i+fHnq0qVLP+tcl52d7QeIiYlxZ511Vi3AAQcc0PjSSy+lhj9+SUlJ9MaNG+NOOOGEBp/PR3R0tHvnnXfizzjjjNof/OAHRc3NzfbnP/85bc6cOfXJycnupZdeSl2zZk3i008/nQFQX18f9dFHH8XHxsa6WbNmNXbtJv2LX/wi5y9/+Us6QGVlZcyHH34YX15eHnPwwQfXd9Z+2mmn1Xz88cfxAK+//nrqJ598ktC5f0NDQ1RNTY0vIyOj7+a+fkyfPv1jn8/nqqurszpDL4Bzrhr4M/BnM9u1/uIyrOJ8PsbHxjI+dvADXznnaAoE+gzK4bdLW1v5oLGRmvb2frtpG8Fu2gMNyuHL1U1bRGR0WHPrrdtDbyd/czNrbr1VwVdkNFn1s/ztobdToMXHqp/l72rw7SubvfLKK6nPP/98+h133DEBoLW11datW9fjh9OTTjppW3Jy8g4tL73lNoDXXnvtk6amJjvttNP2eOaZZ1JPO+203qdBCTMmWnwh+MLceOONhS+88MLazZs3b6/7hz/8Yf6RRx5Z/+KLL366du3a2GOOOWZa57rExMSuAa7HD87R0dHOF+rCGR0dTUdHxw4bPfDAA5l1dXVRhYWF+0IwbD700EOZd9xxR/kXv/jF+ieeeCL1T3/6U8bZZ59dHXosu+2224rnzZvX7Qfx7LPPpnSt6dlnn0159dVXU1asWLEmJSUlMGfOnGnNzc0+10fLm3OOFStWrO7pTbIrfD5fv8dzzg3q3GoZO8yMpKgokqKiyI+LG/T+fueoH8A5zV2D9dqmpu3L++umHWM26HOau95WN20RkaHRXLFDp7g+l4uIR1oqe24J6W35IPWWzZxzPP744+tmz57d2nX71157LSn8GElJST1+AOwtt3VKTEx0X/3qV7c9+eST6cMSfAfSMjucLrvssqq0tDT/nDlzmrs2hdfV1UUVFBS0Adx7771Zve1/1FFH1d1+++3j77///hIINpl3/fagL48//njmk08++clxxx3XCLBmzZrYE044Yeodd9xRftZZZ1X//ve/z1q1alXSY489tgHg+OOPr/3tb3+b/dWvfrU+Li7OrVy5Mm7SpEk7hMZt27ZFpaWl+VNSUgLvvfde/Pvvv58EcMQRRzT++Mc/LtyyZUtUenq6f9myZRl77713M8Dhhx9e94tf/GL8TTfdtAmCI6QdeuihzeHHHqySkpJcgPr6+kQzuyFstXPO3bSrjyGRK8qM9JgY0neym3ZbqLW5v3Oaa7pc70w37Z3pqp0aHa1u2iIiIQm5uTSXl/e4XERGkfgJbbRU7Bhy4yfs0gC9nXrLZkcffXTdbbfdlrN48eJin8/H66+/nnDYYYc1p6am+hsaGgbUEtFTbouNjXXbtm2LmjhxYnt7ezvPPfdc2mGHHVY/mJrHTIvvnnvu2f6Tn/xkc/jyH/7wh5UXXXTR5DvuuGPCEUcc0Wviv+WWWyrmz59fNGXKlH18Pp+77rrryi+44IJt/T3u2rVrY8vLy2OPOeaY7QNITZ8+vS05Odn/j3/8I+m0006ru/TSSycfd9xx2+Lj4x3A9773vaoNGzbE7bvvvns75ywzM7P9r3/966fhx543b17tokWLsqdOnTpjzz33bJk9e3YjwOTJk9u/973vVRx00EF7jx8/vn3q1KnNaWlpfoBFixaVXHTRRUVTp06d4ff77eCDD64/9NBDiwf0IvbB5/N1ntPrgM7nmghcBIwDFHxl2MQOUTft8KDcW8tzWaib9raODmo7OugrNnd20x7MOc1dl6ubtohEkunXXtvtHF+AqIQEpl97rYdVicgO9r2hrNs5vgC++AD73lA2FIfvLZv9/Oc/L1+4cGHR9OnTZzjnrKCgoPXll19ed/LJJ9ffeuutudOnT59xzTXX9NlFpKfcdswxxzR85Stf2autrc0CgYAddthhdd///ve3DKZm66tb7fvvv79h9uzZVYM5oAyN2tpaX1paWqC9vZ0TTzxxrwsvvLDq/PPP3zbcj/v+++9n7bfffvsCVwELgEeB25xzO7yxR1JSUpJrbNzlwatFdhAY6GjaPbRC1wywm3ZvQTklOppos34vUdD/NgM4Tn/bqWVbRAZCozrLQDjncAT/zwYInhYVCL/fZZm/y7qAc6RFR5O5i9OR7gwza3LO7dAtdzQYdDYbplGdR7P3338/a/bs2ZN6WjdmWnx3N9///vfzli9fntra2mpHHnlk3Te/+c1tw/2Y7e3tUXV1denASuAB4AvOuUGNliYy1viGoJt2j6Np99Fde0Oom3a930+Hc3SEPhx4zWDwQZqRCeU7td1O1qYWepG+FcydO+xB1w0yJPUYqga4/3Aee6j3H8219bT/rviviRO5afLkXTzKbm7KpdWRHnQHQ8F3lFq0aFHpSD7ehg0bCurq6tLNrBnY1znXMJKPLzJWxfp8ZMfGkr0T3bS76vwA0dHPZUDbQL/bDPRYA37M0HVLILBLtY0GPnYMzEMZygcSyIfiMaPMtre4bL/0cp8BbDPQ+wzBMTp7o+3qMbrVNIqeW6S85l0DUHhI2tUANTr+Ggw/H8EvYKNC19vvd7ntg57vD2Bd+LFjzIjy+QZ87F2tLXz/wRx7VtKobHSVMUzBVwCoqqrKMTPX2NgYC5R3afEwgoNb7TDNk4gMHV/ow8DuPGeY6/IBecSDO0P7ZUFbP18A9HWsAY26KEPOul7Mer3PALYZ6P3BPO6I1UXw71G3db3sM9ggM5QBarj3H4na1LtEZGT1F3wDgUDABjLVjYxtBx544LuBQMBWrVqV4Zzbw+t6RGT3Y6EPj1FmDMlcC2OUCwvFAwnlvYXosR7CGIJjdN6nt20UPkRk7FA260MgEDDovZd9f8H3gy1btszIzs6u1Qsc2QKBgG3ZsiUN+MDrWkREdmdmoe7KXhciIiKjjbJZLwaSZfr8v9rR0XFRZWXl7yorK2cS7NEikSsAfNDR0XGR14WIiIiIiEh3ymZ96jfL9DmdkchooemMRERERGS4jebpjGTX6JsCERERERERiWg6hUgAMLOn+1rvnPvaSNUiIiIiIiIylBR8pdMhQAnwCPAWnw+oKSIiIiIigJndD3wV2Oycmxm27lrg/wHZzrmq0LIfAwsAP/Ad59zzI1yyhKirs3SaAFwHzAR+DRwPVDnnXnXOveppZSIiIiIio8Ni4KTwhWZWSPDzc3GXZTOAs4B9Qvv8xsyiRqZMCafgKwA45/zOueeccxcAXwTWAa+Y2ZUelyYiIiIiMio455YD1T2s+j/gB0DXkYPnAkudc63OufUEP1/PGf4qpScKvrKdmcWZ2enAw8C3gTuAJ7ytyhuly5bx0hFH8Mxee/HSEUdQumyZ1yWJiIiIyChkZl8Dypxz74etyid4KmGn0tAy8YDO8RUAzOwBgt2c/wb8t3Ou18mfI13psmWsvP56/M3NADSXl7Py+usBKJg718vSRERERGR4RZvZii73FznnFvW2sZklAtcDJ/S0uodlmkvWIwq+0uk8oBGYClxlZp2/lAY451yqZ5WNsDW33ro99HbyNzez5tZbFXxFREREIluHc+7AQWy/JzAZeN/MAAqAf5vZHIItvIVdti0AyoeqUBkcBV8BwDmnbu8hzRUVg1ouIiIiIrsn59wqYHznfTPbABzonKsKTRf6RzO7HcgDpgBve1Ko6Bxf6c7MVpnZEjP7oZmdbGYFZna913WNpITc3EEtFxEREZHdg5k9AvwLmGZmpWa2oLdtnXMfAo8CHwHPAd92zvlHplIJZ86pm7l8zswygVmhywEER6P7yDl3qJd1JSUlucbGxhF5rPBzfAGiEhKYdfPN6uosIiIiEsHMrMk5l+R1HTL01NVZunHOVQOvhC6Y2RTgvzwsacR1hts1t95Kc0UFCbm5TL/2WoVeEREREZExSi2+0o2ZTXHOfRK27D3n3P5e1QQj2+IrIiIiIrsntfhGLrX4SrhFZrYnUAasBOKBD8ws0TnX5G1pIiIiIiIig6fgK904544GMLMiYD9gduj6fTPzO+eme1ediIiIiIjI4KmrswBgZub6eTOYWapzrm6kaupKXZ1FREREZLipq3Pk0nRG0ullM7sy1NK7nZnFmtkxZvYAcLpHtYmIiIiIiOw0BV/pdBLgBx4xs3Iz+8jM1gOfAGcD/+ecW9zfQczsJDNba2brzOxHPaxPM7NnzOx9M/vQzOYP9RMRERERERHpSl2dZQdmFgNkAc3OuW2D2C8K+Bg4HigF3gHOds591GWb64A059wPzSwbWAtMcM619XVsdXUWERERkeGmrs6RSy2+sgPnXLtzrmIwoTdkDrDOOfdZKMguBcInv3VAipkZkAxUAx27WrOIiIiIiEhvFHxlKOUDJV3ul4aWdXUXsDdQDqwCrnLOBUamPBERERER2R0p+MpQsh6WhfelPxH4D5BHcJqku8wstceDmS00sxVmtqKjQ43CIiIiIiKyczSPr3RjZnHAPGASXd4fzrmfDWD3UqCwy/0Cgi27Xc0Hfh6aOmldaACt6cDb4Qdzzi0CFkHwHN+BPwsREREREZHPqcVXwi0jeF5uB9DY5TIQ7wBTzGyymcUCZwFPh21TDBwLYGY5wDTgsyGoW0REREREpEdq8ZVwBc65k3ZmR+dch5ldATwPRAH3O+c+NLNLQ+vvAW4CFpvZKoJdo3/onKsaotpFRERERER2oOmMpBszWwTc6Zxb5XUtXWk6IxEREREZbprOKHKpxVfCHQ5cGDr3tpVgq6xzzs3ytiwREREREZGdo+Ar4U72ugAREREREZGhpOAr3TjnNnpdg4iIfM45h2t3BFoDBFoCBFr8n9/evixAoNXfbZkvxsiam0N0iv7Vi4iI6L+h7MDMZgNHhO7+0zn3vpf1iIiMRa7D7RBGP78dvtzfwzafh1kCA3hAA1+cD1+8D1+cj/bqdlorWin49kSiEqOG/fmKiIiMZhrcSroxs6uAi4EnQotOAxY55+70rioNbiUiI8MFXP8htdWPawngDy1zXbfrsq/rGNj/V4s1fPFR2wOrL74zvEZ1ud3XMh+++Cgs1jCz7cdtXNNAxe9KiSuII//SInzxCr8iIv3R4FaRS8FXujGzlcAhzrnG0P0k4F9eD26l4CsivXHO4dpcL12Ae2lJ7XG5H9c2wLAaYzsEz877FucjKj4URrsFWd+OATfOh/ms/wfcSQ2r6qlYXErCHonkXVyIL9Y3bI8lIhIJFHwjl7o6SzgD/F3u+0PLRESGjHMu1BW4SwtpawB/qHXVDSa4tgZgIHnVxw7BMyo5iphxMX23uIaH17goLHps/FlM3jeFnLPz2PTHcioWl5L3rcIxU7uIiMhQUvCVcH8A3jKzJwkG3lOB+z2tSERGDed3fXYB3vEc1Z62Cy7r9hVbb8LOW+0MpNFp0Vi8j6jtraw9dAHu0grri/dh0d27Au8uUg9Mw7UF2PxYJZUPlzHh/PxhbWUWEREZjdTVWXZgZl8ADiMYfJc75/7jbUXq6iyyK1zAEWgLdGtJ9bf4u7Sq9t8FuPO2ax/Eeas9de0NC6N9L9/xvFXZeTUvb6Xq6c2kzklj/Jm5Cr8iIj1QV+fIpRZfAcDMXnPOHW5m9QQ7DVqXdc45l+pddSK7n+1T2AwgjO6wPOw8V9c6kCGBwaJth+AZnRqNjY/FFzpv1XrtAty9xVWhavTJOHocgZYA1S9UYXE+sk/L0ZcKIiKy21DwFQCcc4eHrlO8rkVkd9BS3EztGzW9z8XaMpjzVruH0ajEKGIyYwbX4jqGzluVnZd5UhaB1gDbXq3GF+cj6yvjvS5JRERkRCj4Sjdm9gvn3A/7WyYiO6+1vIWy3xYDEJ0Wvf0c1ZjU6AFPXbO9ZTVGXYFl4MyMrLnjCbQGqHlpK744H5nHZXldloiIyLBT8JVwxwPhIffkHpaJyE5o39pG2b0l+OJ8FFw1iZiMGK9Lkt2MmTH+6xNwbQG2/mULvjgf6Udkel2WiIjIsFLwFQDM7DLgcmCP0Fy+nVKAN7ypSiSydNR3UHZvCa4jQP4VCr3iHfMZOefkEWgLsOWJTfjifKTOSfe6LBERkWGjUZ0FADNLAzKAW4AfdVlV75yr9qaqz2lUZxnrAi1+Su8upm1TK/mXFZEwOdHrkkQItAcov6+E5nVNTDg/n5T9NI6hiOzeNKpz5FLwlR2YWQYwBYjvXOacW+5dRQq+MrYFOgKU31dK87pGcr9VQPI+GkNORo9Aa4Cye4ppKWkm71uFJM1I9rokERHPKPhGLp/XBcjoYmYXAcuB54H/Dl3/1MuaRMYyF3Bs+mMFzR83knNmrkKvjDq+OB95CwuJmxBHxeJSmtbpS0YREYk8Cr4S7irgIGCjc+5oYH9gi7cliYxNzjm2PLmJhvfqGPfV8TqHUkatqIQo8i4tIiYzhvLfldKysdnrkkRERIaUgq+Ea3HOtQCYWZxzbg0wzeOaRMakmpe2UvtaDelHZZJxjEbNldEtOjma/MuKiE6OomxRMa3lLV6XJCIiMmQUfCVcqZmlA08BL5rZMqDc04pExqDaf9Ww9a9bSDkglaxTxmuuXRkTotNiyL+8CF+Mj7LfFtO2udXrkkRERIaEBreSXpnZkUAa8Jxzrs3LWjS4lYwlDSvrqFhcRuL0JPIWFGJRCr0ytrRtaqX0ro1YtFFw5SRiMjX1lojsHjS4VeRSi69sZ0GFnfedc6865572OvSKjCVN6xqpfKic+KIEci8oUOiVMSk2J478S4uCIz7/diMdte1elyQiIrJLFHxlOxds/n/K6zpExqrWshYqfl9KzLgY8i4uwBenP7EydsXlx5O3sIiOug7K7inB39DhdUkiIiI7TZ/KJNybZnaQ10WIjDXtVW2U3VuML95H3iVFRCVFe12SyC5LmJRA3kWFofd3Cf5mv9cliYiI7BQFXwl3NPAvM/vUzFaa2SozW+l1USKjWUd9B2X3FuP8jrxLiojJ0PmQEjkSpySRe2E+reUtlN9XQqA14HVJIiIig6bgK+E+APYEjgFOCV3WeFqRyCjmb/FTvqiEjtoO8i4uJG5CnNcliQy5pH1SmPDNfFo2NFNxfymBDoVfEREZWxR8JdxezrmNXS4bgOleFyUyGgU6AlTcX0preQu5F+STMCnR65JEhk3K/qmMPzOXpo8bqXywDOfXrBAiIjJ2KPgKAGZ2mZmtAqaFujh3XtYD6uosEsYFHJuWlNP8SRM5Z+WStE+K1yWJDLu0g9PJPi2HxlUNbHqkHBdQ+BURkbFBo69Ipz8CfwNuAX7UZXm9c67am5JERifnHFue3ETDf+rJ+tp4Ug9K97okkRGT/qVMAq0Btv51C744H9lnTMBM03aJiMjopuArADjnaoFa4GyvaxEZ7apfrKL2tRrSj84k4+hxXpcjMuIyjhtHoCVAzT+2YnE+sk4Zr/ArIiKjmoKvdGNmccA8YBJd3h/OuZ95VZPIaFL7Rg3Vf6si5cA0sr463utyRDxhZoz7ajaBtgDbXq7GF+dj3InZXpclIiLSKwVfCbeMYMvvu0Crx7WIjCoNK+vY/HgliTOSyTkrF/OphUt2X2ZG9mk5BFoDVD9XhS/OR8ZR6gEhIiKjk4KvhCtwzp3kdREio03TukYqHywnviiB3AvysSiFXhHzGTln5uJaA1Qt24wvzkfaIRlelyUiIrIDjeos4d4ws329LkJkNGkta6Hi96XEZMWQd3EBvlj96RTpZFHGhPPySdw7ic2PVVL/71qvSxIRGTZmdr+ZbTazD7os+39mtiY0I8qTZpbeZd2PzWydma01sxM9KVoABV/Z0eHAv0O/nCvNbJWZaToj2W21V7VRdm8xvngfeZcUEZWkjjIi4SzayL2wgIQ9EqlcUk7DB/VelyQiMlwWA+G9I18EZjrnZgEfAz8GMLMZwFnAPqF9fmNmUb0d2MyuMDN1mxkmCr4S7mRgL+AE4BTgq6Frkd1OR30HZfcW4/yQf2kRMRkxXpckMmr5Yn3kXlRAXEE8lYvLaFrb6HVJIiJDzjm3HKgOW/aCc64jdPdNoCB0ey6w1DnX6pxbD6wD5vRx+AnAO2b2qJmdZBouf0gp+Eq4YuAI4ALn3EbAATneliQy8vwtfsrvLaajroO8iwuJzYnzuiSRUS8qPor8hUXEjI+l/P4Smj9r8rokEZHBijazFV0uCwe5/7eAv4Vu5wMlXdaVhpb1yDn3X8AU4PfAhcAnZva/ZrbnIGuQHij4SrjfAIfw+Xy+9cDd3pUjMvICHQEq7i+ltaI12H1zUoLXJYmMGVFJUeRfVkR0Wgzl95XQUtLsdUkiIoPR4Zw7sMtl0UB3NLPrgQ5gSeeiHjZzfR3DOeeAytClA8gAHjezXw60DumZgq+EO9g5922gBcA5VwPEeluSyMhxAcemh8tp/qSJnLPzSNo72euSRMac6JRo8i8rwpfgo+zeElorNTueiEQ2M7uA4CmC54bCKwRbeAu7bFYAlPdxjO+Y2bvAL4HXgX2dc5cBBwDzhqXw3YiCr4RrD5107wDMLBsIeFuSyMhwzrHliUoa3q8na+54Ug9M87okkTErJiOG/MsmYj4o+20xbVVtXpckIjIszOwk4IfA15xzXc/xeBo4y8zizGwywW7Mb/dxqCzgdOfcic65x5xz7QDOuQDBUC27QMFXwt0BPAmMN7ObgdeAW7wtSWRkVD9fRe3r28g4ZhwZR43zuhyRMS82O5b8y4pwHY6y3xbTvq3d65JERHaJmT0C/AuYZmalZrYAuAtIAV40s/+Y2T0AzrkPgUeBj4DngG875/y9Hds5d4NzbqOZjTezos5LaN3qYX5qEc8+b4kXCTKz6cCxBM9L+Pto+EVLSkpyjY0aIVSGz7bXa9jyeCUpB6WRc3YuGkhRZOi0FDdT9ptiotKiKbhiItEpmhZMREYnM2tyziV59NinALcDecBmYCKw2jm3jxf1RBq1+Eo3ZvYAUOmcu9s5dxdQaWb3e12XyHCq/08dW/5cSeKMZHLOVOgVGWrxRQnkXVxIR007ZfcU42/qtcFDRGR39j/AF4GPnXOTCTZEve5tSZFDwVfCzXLObeu8Exrcan/vyhEZXk2fNLLp4XLiJyaQe0E+FqXQKzIcEvZMJPdbBbRvaqN8UQmBFoVfEZEw7c65rYDPzHzOuZeB/TyuKWIo+Eo4n5lldN4xs0xgwH3SzOx+M9tsZh/0st7M7A4zW2dmK83sC0NQs8hOaSltoeL3pcRkx5J3USG+WP1JFBlOSdOTmXB+Hi0lzZT/vpRAm8ZOFBHpYpuZJQP/BJaY2a8JTmkkQ0Cf8iTcbcAbZnaTmf0MeIPgkOoDtRg4qY/1JxMc0W4KsBD47U7WKbJL2qraKF9UjC/BR94lhUQlRXldkshuIXlWKjln59H8aRMVD5ThOjTWiIhIyFygCfguwcGwPgVO8bKgSKLRJaQb59yDZrYCOIbg4FanO+c+GsT+y81sUh+bzAUeDM1v9qaZpZtZrnOuYpcKFxmEjroOyu8pxgWg4NtFxKTHeF2SyG4l9cA0XFuAzY9VUrmkjAnn5WM+nWYgIru9GGBG6PZTzrlaL4uJNAq+soNQ0B1w2B2kfKCky/3S0DIFXxkR/mY/5YuK6ajvoODyicTmxHldkshuKe3QDAKtAaqe3szm2ArGn5mr8CsiuyUziwUWAacC6wk2Pk00syeBS51zmgh9CCj4SjdmFgfMAybR5f3hnPvZUD1ED8t67OdmZgsJdocmNjZ2iB5edmeB9gAV95fSWtFK3sWFxE9M8Lokkd1axtHjCLQEqH6hCl+cj6zTcjSquojsjv6LYGtvoXOuHsDMUoC7gZ+ELrKLFHwl3DKgFngXaB2G45cChV3uFwDlPW3onFtE8NsvkpKSdBKY7BIXcFQ+XE7zuiZyvplH0vRkr0sSESDzpCwCLQG2La/G4n1kfXm81yWJiIy004E5zrmmzgXOuXozuxx4EwXfIaHgK+EKnHN9DU61q54GrjCzpcDBQK3O75Xh5pxj8+OVNK6sJ2vueFIPSPO6JJFhU7psGWtuvZXmigoScnOZfu21FMyd63VZvTIzsk4dT6AtQM2LW/HF+cg8NsvrskRERlKga+jt5JxrMDM1/gwRBV8J94aZ7eucW7UzO5vZI8BRQJaZlQI3Euy6gXPuHuCvwJeBdQRHrZs/FEWL9KX6+Srq/rWNjGPGkXHUOK/LERk2pcuWsfL66/E3NwPQXF7OyuuvBxj14Xf81ycQaAuw9dkt+OJ8pB+e6XVZIiIjxYWmE+3pXA/N+zZELDi4rkiQmX0E7EXwxPpWgr+Azjk3y8u6kpKSXGNjo5clyBi17fUatjxeSeqcNMaflavzByWivXTEETSX73j2SEJeHsf9858eVDQ4zu+oWFxK4wcN5JydS+qcdK9LEpHdjJk1OeeSRvgxNxAMuD2OheOc22Mk64lUavGVcCd7XYDIUKn/Tx1b/lxJ0j7JjP+GQq9EvuaKns8c6W35aGNRxoTz8ym/r4RNSyuwOB8ps1O9LktEZFg55yZ5XcPuwOd1ATK6OOc2AukEJ8s+BUgPLRMZU5o+aWTTw+XET0pgwvn5WJRCr0S+hNzcQS0fjXwxPvIWBEddr3yojMbVDV6XJCIiEUDBV7oxs6uAJcD40OVhM7vS26pEBqelpJny35cSMz6WvIsK8cXqT53sHqZfey1RCd2n6YpKSGD6tdd6VNHO8cX5yFtYSNyEOCr+UErTOp3qIiIiu0bn+Eo3ZrYSOMQ51xi6nwT8S+f4yljRtqWN0js2YDE+Cr8zkej0GK9LEhlRY21U5750NHRQdtdG2rd1UHBZkebeFpFh58U5vjIyFHylGzNbBRzknGsJ3Y8H3nHO7etlXQq+MhAdte2U3LGRQGuAwu9MJHZ8nNclicgu6tjWTsmdGwm0+Cn49kTi8uK9LklEIphXwdfMfMBK59zMkX7s3YX6/0m4PwBvmdlPzeynBCfN/r23JYn0z9/sp2xRCf6GDvIvLlToFYkQ0ekxFFxehC/GR9lvi2nb3Op1SSIiQ845FwDeN7Mir2uJVGrxlR2Y2ReAwwkOqb7cOfeexyWpxVf6FGgPUH5vCc3rm8i7uJCk6clelyQiQ6xtUyuld23Eoo2CKycRk6nTGERk6HnZ1dnM/gEcBLwNbP/g65z7mhf1RBoFXwHAzPYCcpxzr4ctPwIod8596k1lQQq+0hsXcFQ8UEbjynpyvplH6gFpXpckIsOktayF0rs3EpUURcEVE4lOU/gVkaHlcfA9sqflzrlXR7qWSKSuztLpV0B9D8ubQ+tERh3nHJsfr6RxZT1Zp+Yo9IpEuLj8ePIWFtFR10HZPSX4Gzu8LklEZMg4517t6eJ1XZFCwVc6TXLOrQxf6JxbAUwa+XJE+lf9XBV1/9pGxnHjyDgy0+tyRGQEJExKIO+iQtqr2ii7twR/i9/rkkREhoSZfdHM3jGzBjNrMzO/mdV5XVekUPCVTn0Nk6n5I2TU2fbPaqpfqCL14DTGfTnb63JEZAQlTkliwoX5tJa1UH5fCYG2gNcliYgMhbuAs4FPCH7+vii0TIaAgq90esfMLg5faGYLgHc9qEekV/Xv1bHlyU0kzUxm/NdzMTOvSxKREZa8TwoTvplPy/pmKu4vJdCh8CsiY59zbh0Q5ZzzO+f+ABzlcUkRQ8FXOn0XmG9mr5jZbaHLqwS/abrK29JEPte0tpHKJWXET05gwnn5WJRCr0hXS5bApEng8wWvlyzxuqLhk7J/KuPPzA3+XXiwHOfXgJ0iMqY1mVks8B8z+6WZfQ/wZKCtSKRRnaUbMzsa6Jw4+0Pn3D+8rKeTRnUWgJbiZkp/U0xMZgwFV04kKiHK65JERpUlS2DhQmhq+nxZYiIsWgTnnutdXcNt2/Jqtjy5iZQDUsk5Jw/z6QsxEdk5Ho/qPBHYBMQC3wPSgN+EWoFlFyn4ypig4CttW9oovWMDFuOj8CpNYyLSk0mTYOPGHZdPnAgbNox0NSOr+sUqtv51C2mHppN9xgSdAiEiO8XL4Bt6/ASgyDm31qsaIpW6OovIqNdR207ZPcXgIP/SQoVekV4UFw9ueSTJOG4cGceMo/aNbWx9ZjP6Yl9ExhozOwX4D/Bc6P5+Zva0p0VFEAVfERnV/M1+yhaV4G/oIG9hIbHj47wuSWTUKioa3PJIYmaM+2o2aYdlUPNyNdUvVnldkojIYP0UmANsA3DO/QdNKzpkor0uQEYXM4sD5hH8Jdv+/nDO/cyrmmT3FWgLUPH7Uto2tZJ3cSHxRZpZS6QvN9/c8zm+N9/sXU0jyczIPj2HQGuA6r9V4YuL0hzfIjKWdDjnanWqxvBQi6+EWwbMBTqAxi4XkRHl/I7Kh8to/qyJCefkkTQt2euSREa9c88NDmQ1cSKYBa8jfWCrcOYzcs7KJXlWClVPbaL2zRqvSxIR6ZOZ/dXMJgMfmNk5QJSZTTGzO4E3PC4vYmhwK+nGzD5wzs3sf8uRpcGtdi/OOTY/Wkndm9vIPi2H9C+pxUZEBsd1OMp/X0LT2kYmfDOPlC+keV2SiIwBXgxuZWbfAP4HeAhIAI4PrXoeuMk51zqS9UQqtfhKuDfMbF+vi5Dd29a/baHuzW1kHD9OoVdksNYvgacmwR99wev1ETyRbx8s2sidX0DCHolULimn4YN6r0sSEemRc+5RYH8gGfgK8CdgKVADfNvD0iKKgq+EOxx418zWmtlKM1tlZiu9Lkp2H9uWV1Pz4lZSv5jOuJOzvS5HZGxZvwTeXghNGwEXvH574W4bfn2xPnIvKiCuIJ7KB8po+lg9h0Rk1GoneHphHMEA3HlJ8bKoSKKuztJNaOLsHTjnepgZcuSoq/Puof7ftVQ+XE7SzGRyLyjAojS4g8igPDUpFHrDJE6EUzeMdDWjhr/RT+ndG2nf2kb+pUUkTE70uiQRGaU86up8EnA78DTwM+dcUz+7yE5Q8JUxQcE38jWubaD8vhLiJyaQf0kRvlh1SBEZtD/6gJ7+rxucExjpakaVjroOSu/aiL++g/zLi4gv1CjxIrIjj4LvP4FLnXMfjuTj7m70yVJ2YGazzeyK0GW21/VI5Gspbqbi/lJic+LIu6hQoVdkZyX2MmFvb8t3I9Gp0eRfVoQvwUf5vSW0VmqsGBEZHZxzRyj0Dj99upRuzOwqYAkwPnR52Myu9LYqiWRtm1spX1RCVHI0+QsLiUqI8rokkbFr9s0QFdaNNyoxuFyIyYgh/7KJ4IOye4ppr2rzuiQRERkh6uos3YQGsjrEOdcYup8E/Ms5N8vLutTVOTJ11LZT8uuNuPYABd+ZRGx2rNcliYx965fA+9dDU3GwpXf2zTB5N5rIdwBaK1oovasYX7yPgisnEpMe43VJIjJKeNHVWUaGgq90Y2argIOccy2h+/HAO845T6c4UvCNPP5mP6V3bqS9up2Cb+t8OxEZWS3FzZT9ppiotGgKrphIdEq01yWJyCig4Bu51NVZwv0BeMvMfmpmPwXeBH7vbUkSaQJtAcrvK6Ftcyt58wsUekVkxMUXJZB3cSEdNe2U31uMv9nvdUkiIjKMFHwl3KvAfKCa4KTZ84FPPa1IIorzOyofKqNlQzMTzs0ncZq+VBURbyTsmUjutwpoq2yj/N4SAq2798jXIiKRTMFXwt0HtDvn7nDO/RqYDvyXxzVJhHDOsfmxCho/aCD7tBxS9k/1uiQR2c0lTU9mwvl5tJQ0U/77EgLtCr8iIpFIwVfCnQE8YGZ7m9nFwOXACR7XJBFi61+3UPdWLZnHjyP9iEyvyxERASB5Vio5Z+XR/EkTlYvLcH6NfyIiEmkUfKUb59xnwFnAnwmG4BOcc7XeViWRYNvyampe2krqIelknpztdTkiIt2kHpRG9hkTaPyogcol5biAwq+ISCTREIYCbB/Nuet/+UwgiuBAV3g9nZGMbfX/rmXLk5tI2jeF8WdMwMy8LklEZAfph2XgWgNUPbOZzbHG+G/kYj79vRIRiQQKvtLpq14XIJGpcU0DlX8sJ2HPRCacl6cPkSIyqmUcM45Aa4DqF6rwxfrIOi1HX9aJiEQABV8BwDm30esaJPK0bGym4g+lxObEkbugAF+Mzq4QkdEv86QsAi0Bti2vxhfvY9yXx3tdkoiI7CIFX+nGzOKAecAkurw/nHM/86omGZvaNrdSdl8JUcnR5C8sJCohyuuSREQGxMzIOnU8gbYA1S9uxeKiyDx2nNdlicgoYGb3E+wpudk5NzO0LBP4E8HPzxuAbzjnakLrfgwsAPzAd5xzz3tQtqDBrWRHy4C5QAfQ2OUiMmAd29opu6cYM8i/tIjotBivSxIRGRQzY/zXJ5C8fypbn93MtteqvS5JREaHxcBJYct+BPzdOTcF+HvoPmY2g+CgsfuE9vmNmaklwCNq8ZVwBc658F9mkQHzN/kpW1SCvylAwbeLiM2O9bokEZGdYj5jwrl5VLQF2PLnTfjifKQelO51WSLiIefccjObFLZ4LnBU6PYDwCvAD0PLlzrnWoH1ZrYOmAP8a0SKlW7U4ivh3jCzfb0uQsamQFuA8t+V0L65jbxvFRBfmOB1SSIiu8SijAkX5JMwJZFNj1RQ/36d1yWJyOiT45yrAAhddw4MkA+UdNmuNLRMPKDgK+EOB941s7VmttLMVpnZSq+LktHP+R2VD5bRsqGZnG/mkTg1yeuSRESGhC/GR96CQuInJlD5UBmNqxu8LklEhk+0ma3oclm4C8fqaUh4TRLuEXV1lnAne12AjD3OOTY/VkHjhw1kz8shZb9Ur0sSERlSvjgfeQsLKbt7IxV/KCX/kiIS9kz0uiwRGXodzrkDB7nPJjPLdc5VmFkusDm0vBQo7LJdAVA+FEXK4KnFV7oJTWtUB+QAE7tcRHq19S9bqHurlswTskg/PNPrckREhkVUQhR5lxYRkxlD+X0ltBQ3e12SiIwOTwMXhG5fQHCw2M7lZ5lZnJlNBqYAb3tQn6DgK2HM7CJgOfA88N+h6596WZOMbjWvVlPz962kHpJO5klZXpcjIjKsopOjyb+0CF9SFGX3FtNa3uJ1SSIygszsEYKDU00zs1IzWwD8HDjezD4Bjg/dxzn3IfAo8BHwHPBt55zfm8rFnFM3c/mcma0CDgLedM7tZ2bTgf92zp3pZV1JSUmusVGzKo02de/WsunhcpJnpTDhgnzM19OpLCIikad9axsld26EgKPgionEjo/zuiQRGQJm1uSc00AlEUgtvhKuxTnXAmBmcc65NcC0ge5sZveb2WYz+6CX9eeGBs1aaWZvmNnsIapbRljj6gY2/bGchL0SyflmnkKviOxWYsbFUnBZEQSg7LfFtFe3e12SiIj0QcFXwpWaWTrwFPCimS1jcCfhL2bHSb27Wg8c6ZybBdwELNq5MsVLLRubqVhcSlxuHLnfKsAXoz8lIrL7ic2JI+/SIgItAcp+u5GOWoVfEZHRSl2dpVdmdiSQBjznnGsbxH6TgGedczP72S4D+MA51+98ZurqPHq0bWql5M6NRMX7KPjOJKJTNTi8iOzemjc0Ufbb4mAr8LeLiErS30WRsUpdnSOXmmmkV865V51zTw8m9A7SAuBvw3RsGQbt29opu7cYM8i7tEihV0QESJiUSN5FhbRvaaPs3hL8LRq7RkRktFHwFQDMrN7M6kKX+i73682sbhge72iCwfeHfWyzsHPy8I6OjqEuQQbJ3+in/N4SAk0B8i4pIjYr1uuSRERGjcQpSUy4MJ/WshbK7ysh0BbwuiQREelCXZ1lyPXX1dnMZgFPAic75z4eyDHV1dlbgbYAZb8tprWkhbxLCkmcoh5AIiI9qX+vjsqHykiclkTuggJ80WpjEBlL1NU5cumvsXRjZvFmdrWZPWFmfzaz75pZ/BAevwh4AjhvoKFXvOX8jsoHymjZ2EzON/MUeofAkiUwaRL4fMHrJUu8rkhEhkrK/qmMPzOXpjWNVD5YjvOrgUFEZDRQi690Y2aPAvXAw6FFZwMZzrmvD3D/R4CjgCxgE3AjEAPgnLvHzH4HzAM2hnbpcM4d2N9x1eLrDeccm5ZWUP92LdlnTCD9sAyvSxrzliyBhQuhqenzZYmJsGgRnHuud3WJyNCqebWaqqc2kXJgGjln52rKN5ExQi2+kUvBV7oxs/edc7P7WzbSFHy9UfXMZmr+sZXME7MYd1K21+VEhEmTYOPGHZdPnAgbNox0NSIynKpfqGLr37aQdlg62fMmYKbwKzLaKfhGLnV1lnDvmdkXO++Y2cHA6x7WIx6peWUrNf/YStphGWSemOV1ORGjuBjOPnQJ6381Cf/DPtb/ahJnH7qE4mKvKxORoZZx/DgyjhlH7evb2PrsFtTYICLiHc1FIuEOBs43s86P4UXAajNbBTjn3CzvSpORUreilqplm0menUL26TlqpRhCV5yyhFtOXUhSXLCv86Tsjdx30UKysgDU11kkkpgZ476aTaA1QM0/tuKL85F5gr5IFBHxgro6SzdmNrGv9c65HjppDj91dR45jasbKP9dCQl7JJJ3SaFGJB1iDUsmkWw7/ho1uIkkn7th5AsSkWHnAo5Nj1RQv6KWrFNzyDgy0+uSRKQX6uocudTiK9045zaa2WzgiNCifzrn3veyJhk5LRubqVhcSlxunKbhGCbJ1nOf5t6Wi8jYZz4j56xcXFuAqqc24YvzkfbFdK/LEhHZrehTrXRjZlcBS4DxocvDZnalt1XJSGjb1ErZohKiU6PJu6SIqPgor0uKTIlFg1suIhHBooyc8/JInJ7E5kcrqP93rdcliYjsVhR8JdwC4GDn3A3OuRuALwIXe1yTDLP2mnbK7inGoiD/kiKiU9QZZNjMvhmiErsvi0oMLheRiOaL9pE7v4CEPRKpXFJOwwf1XpckIrLbUPCVcAb4u9z3h5ZJhPI3+im/t5hAS4D8S4qIyYr1uqTINvlcmLMIEicCFryesyi4XEQini/WR+5FBcQVxFP5QBlNH2v8ChGRkaDBraQbM7sauAB4kmDgnQssds79ysu6NLjV8Ai0BSj7bTGtpS3kXVJI4l4ay0FEZCT4GzsovbuY9q1t5F9WRMKkxP53EpFhp8GtIpeCr+zAzL4AHB66+0/n3Hte1gMKvsPB+R3lvy+haU0juRfmkzwr1euSRER2Kx11HZTetRF/fQf5355IfEG81yWJ7PYUfCOXujpLT/yAAwKhi0QY5xybllbQtLqR8WdMUOgVEfFAdGo0+ZcV4UvwUX5PMW2bWr0uSUQkYin4SjddRnXOQqM6R6ytz2ymfkUtmSdlkXZohtfliIjstmIyYsi/bCL4oPS3xbRXtXldkohIRFJXZ+nGzFYChzjnGkP3k4B/OedmeVmXujoPnZqXt1L19GbSDs8g+/QczDR2mYiI11orWii9qxhfvI/CKycSnR7jdUkiuyV1dY5cavGVcBrVOYLVvbONqqc3kzw7hezTFHpFREaLuNx48i8pJNDop/S3xXTUd3hdkohIRFHwlXB/AN4ys5+a2U+BN4H7vS1JhkLjRw1sWlpBwpREcr6Zh/kUekVERpP4ogTyLi6ko6ad8nuL8Tf7+99JREQGRF2dZQddRnU2YLlGdR77mjc0UfabYmJz4ij4dhG++CivSxIRkV40rmmg/HclxBcmkH9pEb44tVOIjBR1dY5c+ksq3ZjZ34EJzrk7nHO/ds69Z2aLvK5Ldl5rZSvl95UQnRZN3sJChV4RkVEuaXoyuefn01LcTPnvSwi0a4IFEZFdpeAr4SYDPzSzG7ssO9CrYmTXtIe6y1mUkX9pEdEp0V6XJCIiA5A8K5Wcs/Jo/qSJygfKcH710BMR2RUKvhJuG3AskGNmz5hZmsf1yE7yN3ZQfm8xgZYA+ZcUETMu1uuSRERkEFIPSiP7jAk0fthA5ZJyXEDhV0RkZ6n5R8KZc64DuNzMLgReAzTR6xgTaA1Qfl8p7VvbybukkLj8eK9LEhGRnZB+WAauNUDVM5vZHGuM/0auBicUEdkJCr4S7p7OG865xWa2Cvi2h/XIIDm/o+KBUlqKm8m9MJ/EvTQ+g4jIWJZxzDgCrQGqX6jCF+cj61RNRyciMljq6izdOOfuDbv/rnPuW17VI4PjAo5NSytoWt3I+K9PIHlWqtcliYjIEMg8KYv0L2WwbXkN1c9VeV2OyLApXbaMl444gmf22ouXjjiC0mXLvC5JIoRafGUHZjYbOCJ095/Oufe9rEcGruqZzdSvqGXcydmkHaIe6iIikcLMyDo1p1vLb8Yx47wuS2RIlS5bxsrrr8ff3AxAc3k5K6+/HoCCuXO9LE0igFp8pRszuwpYAowPXR42syu9rUoGouYfW9n2SjVph2eQcbw+DImIRBqz4Dm+yfunUvXMZra9XuN1SSJDas2tt24PvZ38zc2sufVWjyqSSKIWXwm3ADjYOdcIYGa/AP4F3OlpVdKnure3UfXMZpL3TyX7NJ37JSISqcxnTDg3j4q2AFser8QX6yP1IE3AIJGhuaJiUMtFBkMtvhLOAH+X+/7QMhmlGj6sZ9OfKkiYmkTOORrtU0Qk0lmUMeGCfBKmJLLpkXIaVtZ5XZLIkEjIzR3UcpHBUPCVcH8A3jKzn5rZfwNvAr/3uCbpRfP6JiofKCMuP568+fn4ovUrLSKyO/DF+MhbUEj8xAQqHiyjcXWD1yWJ7LLp115LVEJCt2VRCQlMv/ZajyqSSGLOaTJ06c7MvgAcHrq73Dn3Hw/LASApKck1NjZ6Xcao0lrRSuldG4hKiqbgyolEp+jMBRGR3Y2/2U/Z3Rtp29xG/iVFJOyZ6HVJIrukdNky1tx6K80VFSTk5jL92mtHdGArM2tyzmkuyAik4CvdmNnXgeecc/Vm9hNgf+Am59x7Xtal4Ntde007pb/egAs4Cq+aRMy4WK9LEhERj3Q0dFB650b8tR3kX15EfFFC/zuJSI8UfCOX+kVKuJ+EQu/hwPHAA8A9HtckXfgbOii7p5hAa4D8S4sUekVEdnPRydEUXFaELymKsntLaK1o8bokEZFRR8FXwnUObPUV4B7n3DJAyWqUCLQGKP9dCR3V7eRdVEhcXrzXJYmIyCgQnR5DweVFWIxR9tti2ra0Dd+DrV8CT02CP/qC1+uXDN9jyW5nyRKYNAl8vuD1Er29ZIgo+Eq4MjO7FzgT+KuZxaH3yajg/I6KxaW0FLcw4fx8ncclIiLdxIyLpeCyIghA2W820l7TPvQPsn4JvL0QmjYCLnj99kKFXxkSS5bAwoWwcSM4F7xeuFDhV4aGzvGVbswsETgJWOWc+8TMcoF9nXMveFnX7n6Orws4Nv2xnPp36xh/5gTSvpjhdUkiIjJKtZS2UHb3RqKSoyi4chLRqUM4+OFTk0KhN0ziRDh1w9A9juyWJk0Kht1wEyfChg0jU4PO8Y1casmTcM1AEnB26H4MsM2zagTnHFVPb6b+3TrGfTlboVdERPoUXxBP3iWFdNQFx4TwN3YM3cGbige3XGQQiovh7EOXsP5Xk/A/7GP9ryZx9qFLKNbbS4aAgq+E+w3wRT4PvvXA3d6VIzX/qGbbq9WkH5FBxnHjvC5HRETGgIRJieQtKKR9Sxtli0rwt/j732kgEosGt1xkEK44ZQn3XbSQSdkb8ZljUvZG7rtoIVecor7OsusUfCXcwc65bwMtAM65GjS4lWfq3t7G1mc3k/yFVLJOzcHMvC5JRETGiMSpSUy4IJ/W0hYqfldKoC2w6wedfTNEhY0xEZUYXC6yi/73G9eTFNfUbVlSXBP/+43rPapIIomCr4RrN7MowAGYWTYwBP8pZbAaPqhn058qgh9czs7DfAq9IiIyOMkzU5hwbh7NnzVR8YdSAh27+C998rkwZ1HwnF4seD1nUXC5yC5Ktp77NPe2XGQwhnC0A4kQdwBPAjlmdjNwBvATb0va/TR/1kTlg2XE5ceTOz8fi1boFRGRnZPyhTQCbY7Nf6qg8qFycs/Px6J24f/K5HMVdGV4JBb1MniautLLrlOLr3TjnFsC/AD4X6AcmOuce9TbqnYvrRUtlP+uhOj0GPIWFuKLj/K6JBERGePSvphO1qk5NK6sZ9PSClxg52f10DyrMmxm34xTV3oZJprOSAAws6fDF4WuHYBz7msjW1F3u8t0Ru3V7ZTcsQGAwu9MJCZTp1eLiMjQqX6hiq1/20LaYelkz5sw6LEjOudZbepyGmZiIixaBOeqEVj64QIOf10H7dva6ajpoKOmnfaadjq2tdNeHbxOjH+arIL/IzquEkssCobeEexhoOmMIpeCrwBgZluAEuAR4C0+D74AOOde9aKuTrtD8PU3dFBy50b89R0UXDGRuLx4r0sSEZEI45xj67NbqPnHVjKOGce4r2YPKvyOhnlWZfQKtAaCQTZ02X57W8f2gBs+cowvwUd0Rgwx6TFEZ8QQnRFNTEYMcQXxxI6PG/HnMJDga2bfAy4i2EC0CpgPJAJ/AiYBG4BvhAaJlVFCwVcACA1odTzBaYxmAX8BHnHOfehpYSGRHnwDrQFKf7ORtopW8i8tImGPxP53EhER2QnOObb8uZLa17cx7svZZB6fNeB9fT7o6aOjGQQ0FGZE295auz3UdtCxrb1bq22gKTzVQnTa52E2OiNm+3V0enB51Cg7pau/4Gtm+cBrwAznXLOZPQr8FZgBVDvnfm5mPwIynHM/HJmqZSA0uJUA4JzzA88Bz5lZHMEA/IqZ/cw5d6e31UU21+Go+EMpraUt5M4vUOgVEZFhZWZknz6BQKtj61+3YLE+Mo7MHNC+RUU9t/gWaeyhMS/Q4t8xzA6itTZhj0Si02OIyYgOtdzGEJ0aHamzUkQDCWbWTrCltxz4MXBUaP0DwCuAgu8oouAr24UC71cIht5JBEd4fsLLmiKdCzg2PVJO09pGxp+VS/LMFK9LEhGR3YD5jJyzcgm0Bah6ahO+eB9pB6f3u9/NN/d8ju/NGntoVHMBR0ddR5cuyANsrU0PttAmTE4gOiN11LfWjgTnXJmZ3QoUA83AC865F8wsxzlXEdqmwszGe1qo7EDBVwAwsweAmcDfgP92zn3gcUkRzzlH1bLN1P+7jnFfyR7QBw4REZGhYlHGhPPyqPh9KZv/VIEv1kfK/ql97tM5gNX110NxcbCl9+abNbCV13prrQ1ed9BR20NrbaLv82C7e7XW9ifazFZ0ub/IObeo846ZZQBzgcnANuAxM/vmyJYoO0Pn+AoAZhYAOk+i7fqmMMA55/r+TzjMIvEc3+qXqtj6ly2kfymDrFNzBj2ypoiIyFAItAUoX1RC8/omcucXqPfRKNNja23n7VDQDTT33lobnR69w7m1MRnRmi6xFwM4x/frwEnOuQWh++cDXwSOBY4KtfbmAq8456aNSNEyIGrxFQCcc0Myp7OZ3Q98FdjsnJvZx3YHAW8CZzrnHh+Kxx5Lat/axta/bCHlC6lkzVXoFRER7/hifeReVEDZb4upfKCMvIsLSZyq2VxGyvbW2i7djne6tTYzeL5t1O7bWjsSioEvmlkiwa7OxwIrCDYgXQD8PHS9zLMKpUdq8ZUhZWZfAhqAB3sLvqERpF8EWoD7BxJ8I6nFt+GDeiruLyVxWhJ5CwqxaP1jEhER7/kbOyi9u5j2rW3kX1ZEwiQNtrirnL9La+22LmF2Z1trM2KISVdr7XAa4HRG/w2cCXQA7xGc2igZeBQoIhiOv+6cqx7mcmUQFHxlyJnZJODZPoLvd4F24KDQdrtN8G3+tImye4uJzY2j4PKJ+OKGpKFdRERkSHTUdVB65wb8Df7gnPL5mlO+L/4Wf6jbccdOtdZ2D7XRaq0dBQYSfGVsUldnGVGhuc9OA44hGHz72nYhsBAgNjZ2+IsbZq3lLZT/roTojBjyLy5U6BURkVEnOjWa/MsmUnrnBsruKabgionE5sR5XZYn+mytDZ1jG2jpYyTkPRO3h1m11op4Ty2+MuT6avE1s8eA25xzb5rZYnaTFt/26jZKfr0RMyj4ziRiMmO8LklERKRXbVvaKL1zA+YzCq6cSMy4sf8FdLgdWmtruk/v01Hb0UNrbdTnIx+nq7U2EqnFN3Ip+MqQ6yf4ric4UjRAFtAELHTOPdXXMcdy8O1o6KD0jo34GzoouHIicbnqNiYiIqNfa3kLpXcX44v3UXjlRKLTx86Xtl1ba7eH2m3dR0Tuq7W2a5hVa+3uRcE3cin4ypDr7xzfLtstJsJbfAOtAUp/s5G2ilbyLy0iYQ8NFCIiImNHS3EzZb8pJiotmoIrJxKdPDrOkvM3+7tM6dOxi621wRGRo1LUWisKvpFsdPz1kohhZo8ARwFZZlYK3AjEADjn7vGwtBHnOhwV95fSWtpC7vwChV4RERlz4osSyLu4kLJ7iym/p5j8b08kKmF4Wz13tbU2Yc+kz1trMztHR47R2Boiuzm1+MqYMNZafF3AUbmknIZ/1zH+rFzSDk73uiQREZGd1rimgfLflRBfmED+pUW7FCL7bK2tCbXWhn087dZam/F5mFVrrQw1tfhGLgVfGRPGUvB1zlH15Ca2/bOGcV/NJvPYLK9LEhER2WUNK+uoWFxGwl6J5F1ciC9mx/DbY2vt9i7IHX231mZ2dkHeMeCqtVZGioJv5FLwlTFhLAXf6her2PrXLaQfmUnW3PGY6RtoERGJDHXvbGPTHytInJFM0t5JwRGRt30ecNVaK2Odgm/k0jm+IkOo9s0atv51CykHpJL1NYVeERGJLKkHpRNoc2x5vJKmjxogiu0jHyfslaTWWhEZtRR8RXqyfgm8fz00FUNiEcy+GSaf2+cuDavq2fxoJYnTk8g5O0/fXouISERKPyyDpBnJmA+11orImKHgKxJu/RJ4eyH4m4L3mzYG70Ov4bf50yYqHywjviie3AsLsCh9CBARkcgVkzF25vQVEQFQ3xORcO9f/3no7eRvCi7vQWt5C+W/KyE6MyY42Ie6dImIiIiIjCr6hC4Srql4wMvbt7ZRdm8Jvjgf+ZcWEZWkThQiIiIiIqONgq9IuMSiAS3vqO+g7N4SXEeAvEuK1O1LRERERGSUUvAVCTf7ZohK7L4sKjG4PCTQ4qd8UQkd29rJu6iQuNy4ES5SREREREQGSsFXJNzkc2HOIkicCFjwes6i7QNbBToClP+hjNbyFnIvyCdhcmLfxxMREREREU+Zc67/rUQ8lpSU5BobG70uAxdwVD5cTsN7deScnUvqnHSvSxIRERGRIWJmTc65JK/rkKGnFl+RAXLOseXJTTS8V0fWKeMVekVERERExggFX5EBqnlpK7Wv1ZB+VCYZx4zzuhwRERERERkgBV+RAaj9Vw1b/7qFlAPTyDplvNfliIiIiIjIICj4ivRgyRKYNAl8PijKC/C7nzWRuHcSOWflYj7zujwRERERERkEBV+RMEuWwMKFsHEjOAclFT5+8vdcXo4rwKIUekVERERExhqN6ixjwkiO6jxpUjD0hps4ETZsGJESRERERMQDGtU5cin4ypgwksHX5wu29IYzg0BgREoQEREREQ8o+EYudXUWCVNUNLjlIiIiIiIyuin4ioS5+WZITOy+LDExuFxERERERMYeBV+RMOeeC4sWBc/pNQteL1oUXC4iIiIiImOPzvGVMWEkz/EVERERkd2TzvGNXGrxFRERERERkYim4CsiIiIiIiIRTcFXREREREREIpqCr4iIiIiIiEQ0BV8RERERERGJaAq+IiIiIiIiEtEUfEVERERERCSiKfiKiIiIiIhIRDPnnNc1iPTLzAJAswcPHQ10ePC4snvQ+0uGk95fMtz0HpPh5NX7K8E5p8bBCKTgK9IHM1vhnDvQ6zokMun9JcNJ7y8ZbnqPyXDS+0uGmr7NEBERERERkYim4CsiIiIiIiIRTcFXpG+LvC5AIpreXzKc9P6S4ab3mAwnvb9kSOkcXxEREREREYloavEVERERERGRiKbgK7sVMys0s5fNbLWZfWhmV4WWZ5rZi2b2Seg6I7R8XGj7BjO7K+xYr5jZWjP7T+gy3ovnJKPHEL+/Ys1skZl9bGZrzGyeF89JRo+hen+ZWUqXv1v/MbMqM/uVR09LRpEh/ht2tpmtMrOVZvacmWV58Zxk9Bji99eZoffWh2b2Sy+ej4w96uosuxUzywVynXP/NrMU4F3gVOBCoNo593Mz+xGQ4Zz7oZklAfsDM4GZzrkruhzrFeBa59yKEX4aMkoN8fvrv4Eo59x/mZkPyHTOVY3wU5JRZCjfX2HHfRf4nnNu+Ug8Dxm9huo9ZmbRQDkwwzlXFQomTc65n474k5JRYwjfX+OA94ADnHNbzOwB4EHn3N9H/lnJWKIWX9mtOOcqnHP/Dt2uB1YD+cBc4IHQZg8Q/EOMc67ROfca0DLy1cpYM8Tvr28Bt4S2Cyj0ynD8/TKzKcB44J/DV7mMFUP4HrPQJcnMDEglGIRlNzaE7689gI+dc1tC918C1CtK+qXgK7stM5tE8JvEt4Ac51wFBP8wE/wgOBB/CHUV/Enon7sIsGvvLzNLD928ycz+bWaPmVnOMJYrY8wQ/f0COBv4k1P3LwmzK+8x51w7cBmwilDLL/D74axXxpZd/Bu2DphuZpNCvQtOBQqHr1qJFAq+slsys2Tgz8B3nXN1O3mYc51z+wJHhC7nDVV9MrYNwfsrGigAXnfOfQH4F3DrEJYoY9gQ/f3qdBbwyK5XJZFkV99jZhZDMPjuD+QBK4EfD2mRMmbt6vvLOVdD8P31J4K9VTYAHUNZo0QmBV/Z7YT+If8ZWOKceyK0eFPo3JPOc1A293cc51xZ6Loe+CMwZ3gqlrFkiN5fW4Em4MnQ/ceALwxDuTLGDNXfr9C2s4Fo59y7w1KsjElD9B7bD8A592moN8GjwKHDU7GMJUP4GewZ59zBzrlDgLXAJ8NVs0QOBV/ZrYS6I/8eWO2cu73LqqeBC0K3LwCW9XOc6M4RKkN/xL8KfDD0FctYMlTvr9AHxWeAo0KLjgU+GtJiZcwZqvdXF2ej1l7pYgjfY2XADDPLDt0/nuD5nLIbG8q/YRaaSSM0AvTlwO+GtlqJRBrVWXYrZnY4wW4xq4BAaPF1BM8xeRQoAoqBrzvnqkP7bCA4MEcssA04AdgILAdigCiCAytc7Zzzj9BTkVFoqN5fzrmPzGwi8BCQDmwB5jvnikfqucjoM5Tvr9C6z4AvO+fWjNyzkNFsiP+GXQpcBbQT/J95oXNu64g9GRl1hvj99QgwO3SMnznnlo7Q05AxTMFXREREREREIpq6OouIiIiIiEhEU/AVERERERGRiKbgKyIiIiIiIhFNwVdEREREREQimoKviIiIiIiIRDQFXxERkTHEgl4zs5O7LPuGmT3nZV0iIiKjmaYzEhERGWPMbCbwGLA/wbnE/wOc5Jz7dCeOFaU5yEVEJNIp+IqIiIxBZvZLoBFICl1PBPYFooGfOueWmdkk4KHQNgBXOOfeMLOjgBuBCmA/59yMka1eRERkZCn4ioiIjEFmlgT8G2gDngU+dM49bGbpwNsEW4MdEHDOtZjZFOAR59yBoeD7F2Cmc269F/WLiIiMpGivCxAREZHBc841mtmfgAbgG8ApZnZtaHU8UASUA3eZ2X7A/2/njm0iBoIwjP4TXEwXpOhqIUZUQA9I9EAvdHC6EJFQAaIAJJLzEtiBK+Dk8XuSA+9KltNPu5pLktvVJ86iF4C9EL4AsF3T8lSS+zHG53qzqp6TfCe5yzzQ8ne1/fNP/wgAV2eqMwBs31uSp6qqJKmq47J+k+RrjDElecg8CAsAdkf4AsD2vSQ5JHmvqo/lPUlekzxW1SnzNWenvADskuFWAAAAtObEFwAAgNaELwAAAK0JXwAAAFoTvgAAALQmfAEAAGhN+AIAANCa8AUAAKA14QsAAEBrf+4A0oMhsQF5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,mesozoojan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,mesozoofeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,mesozoomar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Mesozooplankon Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Surface Mesozooplankon Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average surface microzooplankton concentration (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783f2efbe0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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R5DidzsOsjqE7jz/+eLKIHPH555/HWh2LUmpgK161ireOO45XxozhreOOo3jVKqtDUkoppZTqlogccfbZZ49u3/Z4PKSkpEybPXv2mK7O+/DDD+OeeeaZpM72v/vuu84rrrgiv7P9ADfeeGNuVlbW1H3NDQdF4msFr9fbq+NXrFiRevjhhzc+8cQTqVa8vlJqcChetYp1CxfSXFoKxtBcWsq6hQs1+VVKKaXUgBcXF+ffsmVLXGNjowCsXLkyMTMz09PdeWvWrHG+9tprERNfj8fD8ccf37Rs2bKiSPvbnX322bUff/zxpn2LfBAlvnV1dbajjz563KRJkyaOGzdu0pNPPpkMsGXLluiDDjpo8vz580eOGTNm8rHHHju2/RsxY8aM8e+++64ToKyszJGbm3tI+zlHHHHE+EmTJk2cNGnSxDfffNMF8OqrrybMnDlz3Ny5c0ePHz9+8s0335zzq1/9KqM9hhtvvDH3f//3fzMixbZmzZr4v/71rztWrlyZAvDss88mfutb3zqo/ZhXX3014aSTThoD8OKLLyYeeuihEyZNmjRxzpw5B9XV1dkAcnNzD7ntttuyjzjiiPGPPvpoyr333ps2ZcqUiePHj590+umnH9zQ0GAD2LhxY8y0adMmTJkyZeIPf/jDnNC7Hr/4xS8yp0yZMnHcuHGTfvSjH+X08bdBKbWfNi9ejK+5uUOZr7mZzYsXWxSRUkop1b+MMTR5mqhorGBb9Ta+KP+C93a+x9+++hvPbHiGv3z2F1aXrLY6zEFvx/LlqW8cffQhr4wZc8QbRx99yI7ly/ukge7kk0+ue+6555IBnn766dR58+ZVt++rr6+3nX/++aOmTJkyceLEiZOefPLJ5JaWFrnnnntyXnnllZQJEyZMeuSRR1JuueWWnAsvvHDkscceO/bcc88d/eqrrya0txrX1dXZzjvvvFHjxo2bNG7cuEnLli1LDr6ue+TIkd0m2Z0ZNOv4Op1O/2uvvbYtNTXVX1ZW5pg5c+aEiy66qBagsLAw9sknn/z6mGOO2fmtb33roMcffzzl+uuvr+6srpycHO9777231el0mvXr18dceOGFB23YsGETwLp161yff/75xgkTJrRt2bIl+pxzzjn4F7/4RaXP5+Oll15KWb169V53GZYvX5584okn1k2dOrU1OTnZ9/777zvPOeec+ptvvnlkfX29LTEx0f/000+nnHfeedVlZWWO//f//l/2u+++uzUxMdG/cOHCrF/96leZixcvLgOIjY31f/rpp1sAysvL7bfeemsVwE033ZSzZMmStIULF1becMMN+ddff33lNddcU/3b3/42vT2OF198MXHbtm2x69at22SM4ZRTThnz97//PX7OnDmNffrNUErts+aysl6VK6WUUlZrT1Qb2hpobGukobWBhrYGGlqD28Hne+3v4hi/8Xf5mj+b9TOm507vp3c49OxYvjx146JFI/2trTaA1srK6I2LFo0EGHXxxZ3mST1x6aWXVt91113ZF1xwQe2mTZucV1111e4PP/wwHuCOO+7Inj17dv1zzz23o6qqyn7kkUdOPPPMM+t/9rOfla5Zs8b1+OOPFwLccsstcevWrXN+/PHHm+Pj482rr76a0F7/7bffnp2YmOjbunXrlwC7du2y70+87Xqc+H5v1ffyN1RucPbFi7abkjGl6dGzHu2ySbud3++XH/7wh3kfffRRvM1mo7KyMrq4uNgBkJub23rMMcc0Axx22GFNO3bsiOmqrra2NrnqqqtGfvnll3E2m42dO3fuOX7q1KnuCRMmtAGMHz++LTk52fvBBx/ElZWVRU2ePLkpKytrr5nYnn322dSbb765EmDevHnVTzzxROqsWbOaTjzxxPoVK1YkXXnllTX/+te/kh544IHif/zjHwn//e9/Y2fMmDEBwOPxyBFHHLEnMb3ssstq2p9/+umncXfeeWduQ0OD3e1220844YQ6gM8//zz+jTfe2AZw9dVX77777rvzAP7xj38kvvvuu4mTJk2aBNDU1GTbvHlzrCa+Sg0ccdnZgW7OEcqVUkqpvmCMwe1x9zpJDT++vawniWq7WEcsCdEJxEfHkxCTQEJ0AiOcIxiZPJKE6MB2Qkxwf/B5+PEJMQmkxvVJ4+SwtfWBB3Lbk952/tZW29YHHsjd38R35syZzcXFxTGPPPJI6imnnFIXuu+dd95JfP3115OXLFmSBdDa2irbtm2LjlTPGWecURsfH7/XZF3vvvtu4ooVK75u305PT9+fmbD3GDQtvg8//HDq7t27HevXr98UExNjcnNzD2lubrYBREdH7/nA7Ha7aS93OBzG5wt8Tk1NTdJ+zKJFizIzMjI8L7zwwna/309cXNwR7fucTmeH3+orr7yy6s9//nNaZWVl1JVXXrk7PK7y8nL7Rx99lLh169a4G264AZ/PJyJi/u///q94/vz51Q8++GBGWlqab+rUqU0pKSl+YwyzZs2qf+WVV7ZHep8JCQl7Xn/BggWjn3/++W1HH31085IlS0b8+9//Toh0TjtjDD/84Q/LfvzjH1d183EqpSwy4bbbWLdwYYfuzva4OCbcdpuFUSmllLJSe6La4yS1tYFGT+dJbWNbI4aeTf7bnqiGJp1pzjRGJ4/ucZLavj8+Op4oe9QB/rRUT7Tu2hUx2eysvLfOOOOM2rvuuiv/jTfe2FJZWbknpzTG8Pzzz2+bNm1aa+jx77//viu8DpfLFfFuijEGEYm0a7/0OPHtacvsgVJXV2dPS0vzxMTEmFdeeSWhtLS0229afn5+6yeffOKaPXt20/Lly1NC68rLy2uz2+088MADI9qT40guvfTS2kWLFuV6vV6ZN2/e1+H7n3jiiZRzzz1391NPPbWzvWz69Onj33jjjfhvf/vbDddff/2oRx55JO3888+vBjjxxBPdt956a8GGDRtipkyZ0trQ0GDbvn171NSpU1vD625qarIVFBR4WltbZcWKFanZ2dkegEMPPbRx2bJlKd///vdrHn300T23w+bMmVN/99135yxYsKA6KSnJv3379qjo6GiTm5urM2UpNUDknXUWEBjr21xWRlx2NhNuu21PuVJKqYHPb/y429xdtpJGTEo7SWrdbe4eJ6pxjri9EtAMVwYHpx78TVkPktT25w7boGkHU70Qk57e1lpZuVe+FJOe3tYX9V933XVVSUlJvhkzZjSHdlOePXt2/b333pu5bNmyQpvNxgcffBB37LHHNicmJvoaGxt7NL/UiSeeWH/fffdlPPpoIP/ctWuXvS9afQf8T7rH4yE6OtpcffXV1XPmzBkzZcqUiZMnT24aPXp0S3fn3n777RUXXHDBQStWrBhx3HHH1beX//CHP6ycN2/ewS+99FLKrFmzGuLi4jrtuxEbG2uOOeaY+uTkZJ/DsffH9dxzz434yU9+0mFw3llnnVXzxBNPpJ5xxhmNJ598ct3zzz8/4tlnn90BgfHFDz/88I758+cf1NbWJgB33XVXSaTE9/bbby+dMWPGxNzc3LaJEyc2NTY22gHuv//+oosvvnj0kiVLsk477bTa+Ph4H8C5555bv3Hjxtjp06dPgEDr9fLly7dr4qtU/2v1tlLhrqCisYLyxvKOj9Zyyq/009jmIilGSG76C8krXyA5NpmkmCSSY5MjPpJik0iKSdK76Uop1Ut+49/TZXd/k9T2enrKGeXcKwHNjM9kTPSYXiWpCdEJuKJdmqiqHhl3ww0loWN8AWwxMf5xN9xQ0hf1H3zwwZ5f/OIXleHlv/71r0sXLFhQMGHChEnGGMnLy2t9++23t82ZM6dh8eLF2RMmTJh06623djmxyT333FN25ZVXFowdO3ayzWYzd9xxR+nll19ee+211+atXLkytaWlxZaZmTn14osvrrrvvvv2Hj/WCTGm87tLa9eu3TFt2jRLu83+5z//iVuwYMGo9evX7/PU1fvD5/MxefLkSc8999x/DznkkL2SUys0NDTYXC6X32azsXTp0pRnnnkm9Z///Od/+6LutWvXpk2bNm1UX9TVl1wul3G73VaHoYY5n9/H7ubdeyeyER41LTUR6xgRN4Ks+Cyy4rNwRbuob62ntqWWupY6altqqW2p7fauvyvKFTEpTo7pPGEO3Y6290kvJ6WUOmB8fl+3XX877Q4cIal1e3p+DeGKcnWegPYiSY2Pjic+Oh67rU/m5VH9RESajDF7dcsdCHqbm+1Yvjx16wMP5Lbu2hUdk57eNu6GG0r2d3zvQNdVLjOgbxn99re/TX/44Yczfve731nSzfrTTz+NPeuss8bOmTOnZqAkvQAffPCB8+abby4wxpCYmOhbtmzZDqtjUmqwMsZQ31ofOYF1f/O8orGCSnclPrN3T5v46Pg9yezkjMmcPPrkPduZ8Zl7nme4MrpNOttbJdqT4PCkuMOjNbCvvLGczVWb95RHijFUnCMuYkIcmjjvtS/kEeuI3a/PXCk19Pj8vr3GmHbVqtpVktrQ1kCTp6nHr+2Kcu2VgOYk5HRMUMPGsHbW0uqKcmmiqoaMURdfXD3UE93eGPAtvqp/aYuvGiqaPc1UuCs6JK6REtryxnJavHuPnIiyRXVMXF1ZexLY0EdmfCbx0fEWvMPI2idI6TJhbqmlrrXzfR5/10vkRdujIyfFMV0nzO3duJ1RzgMyaYVSqmvtrahNnibcbW7cHjfutuB28Hmk/XvKwrZDE9lmb3P3AQSFjzHdKwHtolU1vMwV7cImPRo2qFSPDKUW3+Fo0Lb4KqVUKJ/fx66mXT3qalzXWrfX+YKQ5kzbk7SOLRgbMZnNis8iJTZlUCZnIrKne11eYl6vzzfG0OJt6XWyXFhXuOd5pBsJoRw2R6dJcVcJc/sjPjp+UH5vlOqO3/hp9jR3mYR2maR2lbS2uWn19a7zmiC4ol24olx7vjqjnLiiXYyIG9Hr8akJMQk4o5yaqCqlLKGJr1LKUsYYaltqu+1qXN5Yzi73rojjXxNjEvckrNOypnG66/S9WmWz4rNId6brxFDdEBHiouKIi4ojO2Hf1hZu8bZ0aG3uKmFu31faULqnrLsujjax9TpZDn0kxCTohbfaJ+03hvqy1TT0mN60mrZzRjk7JKTtSWpWfNbeCWvItit677LwOmLsMXqTSSk1ZGjiq/qUiJwB/BGwA382xvw6bP8E4K/A4cBCY8zi/o9S9YcmT1PEZLaisWKvhLbNt/fM+jH2mD2J66jkURyVe1SnXY2dUU4L3qHqTKwjltj4WDLjM/fp/DZfG3UtdV0nzC111LZ+s/1V9Vd7nnc326ogJMYk9jphbu/GnRSTpGMAByhjDB6/p9MWz/1tNW3yNOE3nS4EEVGMPSZispnmTNvnhLR9f1xUnN7EUUqpHtLEV/UZEbEDDwKnAsXAahF52RjzZchh1cBNwNn9H6HaXx6fh0p3ZSCBdUdYpifk0dDWsNf5gpDhytiTtE5Mm9hpV+OkmCRtaRimou3RpLvSSXel79P5Xr93z2zZERPmkMnB2p9vr92+Z1+kbvLhEqITIk8EFhM5WQ5ProdzzwOv37tvCWkPW027m9wtXJQtKmKymRiTSHZCdqCslwlp6H69SaKUUgPDgE987Xb7EWPHjt3T92fVqlXbxo8fH3Hh5RkzZoxfvHhx0fHHH9/zqQAPMI/HQ0ZGxrSLLrqo6sEHH+yTdbMGsBnANmPM1wAisgI4C9iT+BpjKoFKEfm2NSGqcMYYqpure9TVuKop8nwKybHJexLWI3KOiDgRVGZ8JmnONF1/UB1wDpuD1LhUUuNS9+l8n99HQ1tD9zNrt36zr6S+hI2VG/ckzt21CrqiXJEnAovpflbtpJgkYhwx+/TeesJv/N0mpJ0mqT1IWiP18OiKTWydJpvprvSIrabdJaShZcP5JoRSSvWWiBxx1llnVb/00kvb4Ztc59BDD3W//fbb2zo778MPP4wrKiqKvuCCCyLeXX733Xedjz766Ihly5ZFXM2noaHBNnfu3IN27twZY7fbOe2002r/9Kc/9Sq3GvBXoDExMf7Nmzd/2f2RPePxeIiK2r9/cl6vF4ejZx/diy++mDR69OjWl19+OeX+++8vsdn2r0tSX8R/AOUCoT+sxcDMfa1MRBYACwCio3Xd0d5qbGvsdgKoCncFFY0VEWfxjXXEkh2fHZgEKnUss/JnddrVWJe3UUOJ3Wbfk2Tui9AlqXo6s3ZFYwVbqrb0eEmqWEdst121XVEumr3NvZr8yO1xdzs5WThBcEY590o2XVEuchJyvinrZULaXhZtj9beH0opNUDExcX5t2zZEtfY2Cjx8fFm5cqViZmZmV0vBwGsWbPGuWbNGlekxNfj8XD88cc3ddd4eeutt1bMnTu3oaWlRY499thxzz77bOJ3v/vd+p7GPuAT30jee+895y233JLf1NRkS0lJ8S5fvnzHyJEjPQDLli0bcfPNNxc0Njbaly5dun327NlNt9xyS05ZWVlUYWFhdGpqqvfUU0+tX7Nmjevxxx8vBJg9e/aYW2+9teI73/lOw8UXX1ywdu1aV0tLi23u3Lk1v//970sBcnNzD7nwwgur3n777cRTTjml7pVXXkn58ssvNwGsX78+Zv78+Qdt3LhxU3isTz/9dOr1119f8cgjj6T/61//cs2ePdtdUFBwyNq1a79MS0vzARQUFEz54IMPNtvtdq688sqRJSUl0QD33Xdf4WmnneYOj3/x4sUlF1100ejm5mYbwB//+MfCU0891e3z+bj88ssLPvroo4T8/PxWv9/PFVdcsfvKK6+s6eoz60ORrkw6Xy+rG8aYpcBSCCxntK/1DCVtvraOy/J00eXY7dl7+Se72Dt0NZ6aObXTrsYJ0Ql6sanUPrCJjcSYRBJjEiGp9+cbY2jyNPVqZu3dTbv5uuZraltqqWmu2etmVqwjNmKLaIYro2Oy2YuEtL2OOEec/q1QSqkB6KGHSP3lL8ktLyc6K4u2O++k5Npr2e91fU8++eS65557LvnKK6+sefrpp1PnzZtX/eGHH8YD1NfX26666qqCTZs2xfl8Plm4cGHpeeedV3fPPffktLS02CZMmBB/6623lm3atCkuNL+55pprqu69997Mt99+e1tdXZ3tqquuKli3bp0T4I477ii94ooraufOndsAEBsba6ZOndpUVFTUq5axAZ/4tra22iZMmDAJID8/v/XVV1/9+qabbip47bXXtuXk5HgfeeSRlNtuuy33ueee2wHQ1NRk+/zzzzf//e9/j1+wYMHor776aiPAunXrnB9//PHm+Ph4s2TJkhGdvd59991XkpmZ6fN6vRxzzDHjP/7447iZM2c2A8TGxvo//fTTLQDvvPNO4ocffhh3zDHHND/88MNpF1100e7wuhobG+XDDz9MeOKJJ3bW1tban3zyydRTTjnFfdppp9UuX748+eabb979r3/9y5WXl9eWn5/vnTt37uhbbrml4vTTT2/86quvok8//fSxX3/99V7xNzQ02N57772tTqfTrF+/PubCCy88aMOGDZsef/zxlKKiougtW7ZsLCkpcUyZMmXKFVdcsbu1tVW6+sz6UDGQH7KdB5T28WsMOX7jZ3fT7h51Na5ujvy3KjUudU/COjNvZqddjUfEjdDxZkoNcCLBJWSiXeQm5vb6/PaZhxvbGgMzdDvi9PdeKaWGmYceIvVHP2JkSws2gLIyon/0I0YC7G/ye+mll1bfdddd2RdccEHtpk2bnFddddXu9sT3jjvuyJ49e3b9c889t6Oqqsp+5JFHTjzzzDPrf/azn5WGNjzecsstcaH5zauvvprQXv/tt9+enZiY6Nu6deuXALt27erwT6yqqsr+5ptvJv/4xz+u6E3cPU58v7d5c/4Gt7tPp06d4nI1PTphQsR+3O3CuzqvXr069quvvoo76aSTxgH4/X7S09P33Nq+6KKLqgHmzJnT2NjYaKuqqrIDnHHGGbXx8fHdtho+9thjqcuWLUvzer2ya9euqLVr18a2J76XXXZZTftxV1xxRdUjjzySNmPGjKJVq1alrF69eq/W3meffTb5qKOOakhISPBfcsklNYceemiO1+stuuiii6p/+ctf5tx88827ly9fnjpv3rxqgA8++CDxq6++ims/v7Gx0V5TU2MLj7+trU2uuuqqkV9++WWczWZj586dMQDvvfde/Lnnnltjt9spKCjwHnXUUQ0A69ati+nqM+tDq4GxIjIaKAHmAxcdgNcZ8IwxNLQ19Gi92Up3ZcRujc4o556uxhPTJjJ71GwyXZl7JbQZrowDOt5PKTW4hC5JpZRSanj65S/JbU9627W0YPvlL8nd38R35syZzcXFxTGPPPJI6imnnNKh6/I777yT+PrrrycvWbIkC6C1tVW2bdsWsWW2s/zs3XffTVyxYsXX7dvp6el7LpQ9Hg/nnnvuQQsWLKiYNGlSryaNGPAtvuGMMTJmzJjmL774YnOk/eHdrdq3XS7XnplGHA6H8fu/mXiktbXVBrB58+boBx54IPPTTz/dlJ6e7ps3b96olpaWPT8wCQkJe066/PLLa37zm9/krFixouGQQw5pysrK2itzWbFiReqnn34an5ubewhAXV2d/dVXX00488wzG6666qqY0tJSxz/+8Y/kRYsWlQbfG2vWrNkU6QcgNP5FixZlZmRkeF544YXtfr+fuLi4I9rP35fPrK8YY7wicgPwOoHljB41xmwUkWuD+x8SkSxgDZAI+EXkh8AkY0yP++dbqcXbsldX49DW2dB9kdZjdNgce5LXnIQcDs8+vNOuxvHR8Ra8Q6WUUkopNdiVlxMx2eysvLfOOOOM2rvuuiv/jTfe2FJZWbknpzTG8Pzzz2+bNm1aa+jx77//viu8jtD8JpQxptMhNBdddNGogw46qOXOO++s7G3MPU58u2uZ7S9Tp05tqa6udrz11luuU045xd3a2irr16+POfLII1sAnn766ZS5c+c2vP766/EJCQm+ESNG7JWQHnzwwW2PPPKI0+fzsX379qh169a5AGpqauxxcXH+1NRUX1FRkeOdd95JOuGEE/ZekwVwOp3mhBNOqLvlllsKHnjggR3h+6urq21r1qyJLykpWRcXF2cA/vjHP4546qmnUs8+++yGOXPm1F5//fX5Y8aMaW5PmmfNmlX/m9/8JuNXv/pVBQRmPzvmmGP2yp7q6urseXl5bXa7nQceeGCEzxd4i8cdd1zjE088MeKGG27YXVpa6vj4448TLrzwwuruPrO+ZIz5G/C3sLKHQp6XE+gCPeD98aM/8lHJRx2S29qW2ojHpjnT9iSsxxYcG7GrcVZ8FilxKbrmolJKKaWUOqCysmgrK9s7yc3KondT63fiuuuuq0pKSvLNmDGjObSb8uzZs+vvvffezGXLlhXabDY++OCDuGOPPbY5MTHR19jY2KOL4BNPPLH+vvvuy3j00UeLINDVOT093XfTTTfl1NfX21esWLFjX2IedC2+sbGxZsWKFf+96aabChoaGuw+n0+uu+66ivYkLiUlxXfYYYdNaJ/cKlIdp556auODDz7YOn78+Mnjx49vnjRpUhPA0Ucf3TxlypSmsWPHTi4oKGg94ogjGruK5bLLLqv++9//nnLuuefu1Vr55JNPphxzzDEN7UkvwPz582vvvvvuvObm5sKLL764+oQTTpi4ZMmSHe37ly5dWnT11VcXjBs3bpLP55OZM2c2HHPMMYXhdf/whz+snDdv3sEvvfRSyqxZsxri4uL8EGiFfuuttxLGjRs3efTo0S3Tpk1zJycn+7r7zFRkq0tX82npp2TFZ3FIxiGcetCpgbGyYd2NM1wZuhyGUkoppZQaMO68k5LQMb4AsbH477yTPlle9eCDD/b84he/2KvV9de//nXpggULCiZMmDDJGCN5eXmtb7/99rY5c+Y0LF68OHvChAmTbr311rKu6r7nnnvKrrzyyoKxY8dOttls5o477iidNWuW+/77788ePXp0y+TJkycBLFiwoPKWW26JvNZmBNJZ91iAtWvX7pg2bVqPKxtu7rzzzsy6ujr7H//4xwEzgVNdXZ0tKSnJX15ebp8+ffrEDz74YHNBQYG3p+evXbs2bdq0aaMOYIj7xOVyGbd771mKlVJKKaWU6isi0mSM2atb7kDQ29zsQM3qPJB1lcsMuhbfgeLUU089eOfOnTH//ve/t1odS6hTTz11bH19vd3j8ciPf/zjst4kvUoppZRSSqmh4dprqR7qiW5vaOK7j958883/Wh1DJJ988skWq2NQSimllFJKqYFEZ9lRSimllFJKKTWkaeKrlFJKKaWUUmpI08RXKaWUUkoppdSQpomvUkoppZRSSqkhbcAnviJyxNlnnz26fdvj8ZCSkjJt9uzZY/qifqfTeVhPjz355JMPPvTQQyf0xesOdCLiEhG71XEopZRSSimlBoZ9zc0+/PDDuGeeeSaps/3vvvuu84orrsjvqo7jjjtu7Pjx4yeNGTNm8kUXXVTg9fZu8ZoBn/jGxcX5t2zZEtfY2CgAK1euTMzMzPT0pg6Pp1eHR1RVVWXfuHGjq76+3r558+bo/a2vt9+oA80Yw65du1J3796dISKVwGagTEQ2isjvRGSs1TEqpZRSSimlrLOvudmaNWucr732WsTE1+PxcPzxxzctW7asqKs6Vq1a9d8tW7Z8uXXr1o27d++OevTRR1N6E/uAT3wBTj755LrnnnsuGeDpp59OnTdv3p71qN5++23nYYcdNmHixImTDjvssAlr166NAViyZMmIOXPmHHTSSSeNOe6448bV1dXZzjvvvFHjxo2bNG7cuEnLli1Lbq/jxhtvzB0/fvykadOmTSgqKoq4xNMTTzyRcsopp9Sec8451Y899lgqwLe//e2DQu9czJs3b9SyZcuSvV4v11xzTd6UKVMmjhs3btLvfve7NIBXX301YebMmePmzp07evz48ZMBTjnllIMnT548ccyYMZMXL16c1l7X73//+7RRo0ZNmTFjxvj58+ePvOyyywoASktLHaeffvrBU6ZMmThlypSJb7zxRp8ssL1p06bxLS0tMYmJibVAljEm3xiTARwHfAT8WkQu6YvXUkoppdTgVbxqFW8ddxyvjBnDW8cdR/GqVVaHpJSK5KuHUnkx5xCesh3BizmH8NVDqX1RbVe5WX19ve38888fNWXKlIkTJ06c9OSTTya3tLTIPffck/PKK6+kTJgwYdIjjzyScsstt+RceOGFI4899tix55577uhXX301ob3VuLO8LTU11Q/g8XjE4/GIiPQq7kGR+F566aXVzzzzTEpTU5Ns2rTJefTRR7vb902bNq3lk08+2bxp06Yv77rrrpKf/OQnee37Pvvss/inn356+0cffbT19ttvz05MTPRt3br1y61bt3757W9/uwGgubnZdvTRRzdu2bLly6OPPrrx/vvvT48Uw3PPPZd6ySWXVF9++eXVL7zwQirABRdcUP3MM8+kALS0tMgHH3yQeN5559X94Q9/SEtKSvJt2LBh09q1azc99thj6e2txOvWrXP97ne/K/nvf/+7EWD58uU7Nm7cuOmLL7748uGHH84sLy+379ixI2rx4sXZH3/88ab33ntv61dffRXbHsc111yTf8stt1Rs2LBh08qVK/977bXXjuqLz3jChAlb8/Pzy6KiotqMMf72cmNMtTHmBWPMPOCZvngtpZRSSg1OxatWsW7hQppLS8EYmktLWbdwoSa/Sg00Xz2Uyqc/GklLWTQYaCmL5tMfjeyL5Ler3OyOO+7Inj17dv2GDRs2vffee1t+/vOf57W1tcnPfvaz0rlz59Zs3rz5y+9///s1AOvWrXO+/vrr21555ZXtofV3lrcBzJo1a2x6evo0l8vlu/LKK2t6E3fE1s1IKp4uzW8tb3X2pvLuxGTFNGVemNNlkzbAzJkzm4uLi2MeeeSR1FNOOaUudF91dbX9ggsuGL1jx45YETEej2dP6n/cccfVZ2Zm+gDefffdxBUrVnzdvi89Pd0HEBUVZebPn18HcMQRR7jfeuutxPDXLyoqcuzcuTPmtNNOa7TZbDgcDrN69erY8847r+4nP/lJQXNzs7zwwgtJM2bMaIiPjzdvvfVW4ubNm50vv/xyCkBDQ4P9yy+/jI2OjjZTp051T5gwoa297t/85jeZr732WjJAeXl51MaNG2NLS0ujZs6c2dAe+znnnFOzdevWWIAPPvgg8auvvoprP7+xsdFeU1NjS0lJ8bMfbDab6e4YY8z+9xlXSiml1KC1efFifM3NHcp8zc1sXryYvLPOsigqpdRe1v8yF39Lx0ZOf4uN9b/MZey11Z2c1SNd5WbvvPNO4uuvv568ZMmSLIDW1lbZtm1bxGGiZ5xxRm18fPxeOUhneRvA+++//1VTU5Occ845B73yyiuJ55xzTn1P4+5x4mu1M844o/auu+7Kf+ONN7ZUVlbuifunP/1p7gknnNDw5ptv/nfLli3RJ5100vj2fU6nM7TlkkjN4Q6Hw9hstvbneL3evQ567LHHUuvr6+35+fmHQCDZfOKJJ1KXLFlSetRRRzW8+OKLic8880zKhRdeWB18Lbn33nsL582b1+Eb8eqrryaExvTqq68m/Pvf/05Ys2bN5oSEBP+MGTPGNzc324zpPAc1xrBmzZpNkX5I9kdRUVE2QENDg1NE7tz7Zc2v+vL1lFJKKTX4NJeV9apcKWWRlvLIcxJ1Vt5LneVmxhief/75bdOmTWsNPf7999/fa3imy+WK2HDXWd7Wzul0mu985zu1K1euTD4giW9PWmYPpOuuu64qKSnJN2PGjOZXX301ob28vr7enpeX1wbw8MMPp3V2/oknnlh/3333ZTz66KNFALt27bKH3j3oyvPPP5+6cuXKr0455RQ3wObNm6NPO+20cUuWLCmdP39+9V/+8pe09evXu5577rkdAKeeemrd//3f/6V/5zvfaYiJiTHr1q2LGTVq1F6tpbW1tfakpCRfQkKC//PPP49du3atC+C4445z/+xnP8vftWuXPTk52bdq1aqUiRMnNgPMmjWr/je/+U3Gr371qwoIzJB2zDHHNIfX3Vs2m80PICIGaO+u4ASuBkYAmvgqpZRSw1xcdnagm3OEcqXUABKb1Rbo5hyhvA90lpvNnj27/t57781ctmxZoc1m44MPPog79thjmxMTE32NjY09GmYbKW+Ljo42tbW19pEjR3o8Hg//+Mc/ko499tiG7uoKNSjG+AIcfPDBnl/84heV4eU//elPy+++++68ww8/fILP13kee88995TV1tbax44dO3n8+PGT/va3vyV0enCILVu2RJeWlkafdNJJe/quT5gwoS0+Pt73r3/9y3XOOefUr169OmHWrFn1sbGxBuBHP/pR1YQJE1oOOeSQiWPHjp38/e9/f2RoF+x28+bNq/N6vTJu3LhJd9xxR860adPcAKNHj/b86Ec/Kps+ffrEY489dvy4ceOak5KSfABLly4t+uyzz1zjxo2bdPDBB09+4IEHIo5J7q3c3NyK3Nzcivj4+HpgKRAHfA9YARzUF6+hlFJKqcFtwm23YY+L61Bmj4tjwm23WRSRUiqiQ+4swRbbsUXVFuvnkDtL+qL6znKzX//616Ver1cmTJgwaezYsZN//vOf5wLMmTOnYevWrXHtk1t1VXekvK2+vt727W9/e8y4ceMmTZw4cXJaWprnxz/+8a7exCxddatdu3btjmnTplX1pkLVN+rq6mxJSUl+j8fD6aefPuaKK66ouuyyy2oP5Gt6PB77Rx99NPr444+vAR4D/miM6dWg8QPF5XIZt9vd/YFKKaWUOmC8fj9bV65k5+9/j7e8nKisLHJ+9COy5s4lSgSHyJ6vdpEuuysqNRCJSJMxpk9WTelrvc7NvnoolfW/zKWlPJrYrDYOubNkf8f3DnRr165NmzZt2qhI+wbNGN/h5sc//nHOu+++m9ja2ionnHBC/SWXXFJ7IF9vx44defX19cki0gwcYoxpPJCvp5RSSinr+I2h3utlt9dLtcfDbo+nw/NqrzdQFva8zueDESPgf/+3Y4UffhjxdUIT4ajQ5zZbr/btOaaLfe3ndrVvr9faj3gcmtirgW7stdVDPdHtDU18B6ilS5cW9+frVVVVZYqIcbvd0UBpyB9yITC51V6zXSullFLKWsYY3D5fxEQ1Ylkwwa3xeOhqopNkh4NUh4MRUVGkOhyMjYvb83xEVBTJjsAlpNcYPMGH1xg8fv+esvCvXe1rP7f9uTv82JB9kc7zGtPl+zlQHJ0l2T1MxPsrSd/Xmwaa2KuhRBNfBcCRRx75KQS6BxhjRlkcjlKDljEGX/BiLPTCLNJzARLtdhIcDuLtdux6gaHUsNbq93eaqIY+D2+hbeti2JrLZgskrFFRjHA4yI+P3/M8NSqKEWHPUx0OUhwOHLZBMw3MHv4If28jJdv7m6T3JoHvLElv9vup9/l6FasVib0depWI92WSflRiIscmJVnwrtVQ1V3i6/f7/dKTNV7V4Of3+wXYr/WAlYok0sVI6D/5niSJ3k7O6/K4HpzT5evuY3z7ymWzkehw7EmGE+12Eux2Eh2OPV97Uuay27FpEq2UZbx+P9XtCWovuhI3+Tv/FxwtEkhSg4nqOKezQwts6PM9X6OiiBmECey+sokQLUKfrNUyAJmw/zt93creWZLu6WZfpHhawurtSazh/z9/MXKkJr5709ysC93lMt0lvht27do1KT09vU4/4KHN7/fLrl27koANVscyHPSmVXAoJIlW3k2JNCYr9HnoXefwO85Oh6PjcZ2c01X9Xb2WMYYGn496n48Gr5d6n496r7dD2S6Pp0NZTxJrARJ6mDQn2O0kdlEWZ7NpVzc1bPmNoa6rbsOddCWu62KVCTt0aF0tiI3l0EjJazDBbX/u1N/FYU/aW0MJLL0x1LRfG7VfPzj05z0Szc060ZNcpsvE1+v1Xl1eXv7n8vLyKQyipY/UPvEDG7xe79X7U4mInAH8kcD/9j8bY34dtv9i4KfBzUbgOmPM2v15zQPlvqIi1jY2HpAkcX9aBfeXHfY5aXPa7Z0ndAcwQdzX1xpqXYeNMbQGu8eFJ8j1Pl9gu/15hLKy1tYOZT25IWGDHiXI4WXtLdahZTF64a4sYoyhsbNxsF10Ja7p5vckJWQcbFpUFOPbx8F20ZU40W7X3wOlIpD2/99WBzKAaW7WpW5zmS6XM1KqN0TEDmwFTgWKgdXAhcaYL0OOOQbYZIypEZE5wN3GmJnd1W3FckaXb9rEu3V1PUq4ukrA+jpB3J/X0qUlVDtjgmPMwhLkDslzD8oagmU9+U/iENkrGY6UIId3845UFj2Mum+qjlp8vk67D3fVldjTxfVOvN3e5ZjXSF2JU6KihtzNNaXUwF7OSO0fTXwVACLyclf7jTFn9qCOowkksqcHt38WPPeeTo5PATYYY3K7q1vX8VVq4PKbwKyyDWEt0eEJclddutvL3F2McQwVI9KjBLkn46UH4yQ+Q4HH76emlzMR7/Z4aO7iZyRGQsbBRhjzGqkrcWpUlN5IUUrtoYnv0KW9CVS7o4Ei4GngYwLDBHsrN1hHu2Kgq9bcq4C/d7ZTRBYACwCio4fqVBVKDX62YBKa4HCQExOzX3X5gl1Se9p9O7SsrK2Nrc3Ne/Z1lSCFirPZejV5WGdlw3Vmbr8x1IYlrT2Zibi+i3GwDpEOSevI2FgOCxvzGqmF1mm39+M7V0opNZho4qvaZRHoonwhcBHwGvC0MWZjL+qIdMUXsUuBiMwmkPjO6qwyY8xSYCkEWnx7EYdSapCyi5DkcJDk2P9/T16/f09X7K66akdqnS5qbe1Q1trD3lHtM3P3dPKwzsqsmJm7fbK13s5EXOP1dtrVXQiOgw0mpxnR0Ux0ubrtSpyg42CVUgOUiDwKfAeoNMZMCdt3G/A7IN0YUxUs+xmBa14fcJMx5vV+DlkFaeKrADDG+IB/AP8QkRgCCfA7IvJLY8z9PaymGMgP2c4DSsMPEpGpwJ+BOcaY3fsXuVJKReaw2Uix2UiJitrvutqCSfS+dN/eHmzdbC/raqxpOyEw7rS7cdBdlcXabHtaYnvSlbi7cbAJdnuH5HRUbGy3MxEnOxzDshVcKTWkLQMeAB4PLRSRfAKNSIUhZZOA+cBkIAd4S0TGBa+7VT/TxFftEUx4v00g6R0FLAFe7EUVq4GxIjIaKCHwi35R2GsUBOu81BiztQ/CVkqpAy7aZmOEzcaIPkiiW0MnFetBl+7QfeVtbR3K9uXKKc5m69DKOql9PdguZiJO0QnFlFIKAGPMuyIyKsKu3wM/AVaFlJ0FrDDGtALbRWQbMAP4zwEPVO1FE18FgIg8BkwhMOb2f4wxvV7P1xjjFZEbgNcJrJrzqDFmo4hcG9z/EHAnMAL4U7Abm9cYc2QfvY0+U7xqFZsXL6a5rIy47Gwm3HYbeWedZXVYaghp3NhA7TvVAIhNwA5il+BzQWwEvwpiB2wSsp9guYAtwnl7jg2tI/KxgfLAa+z12uGvZ9OWu74QY7ORHh1N+n7W0z4zd2ct0c0+HykRuhLH6ThYpZTqUyJyJlBijFkbNkwjF/goZLs4WKYsoImvancp4AbGATeLSHt/NwGMMSaxJ5UYY/4G/C2s7KGQ51cD+7VW8IFWvGoV6xYuxNfcDEBzaSnrFi4E0ORX9YnWslbKHy/BHu/AkeTAeAzGZzB+Az6D8YPxGfAHnhPcFygL7rNi1LsQSJ73JNJ7J8zflEvYsV0n3Xsl9hGT/JDX2+s8Ok/y259HjDnCjYRB0jVXgmtrO+12MnUCQKWU6isOEVkTsr00OO9MRCLiBBYCp0XaHaFM562xiCa+CgBjjPZhC9q8ePGepLedr7mZzYsXa+Kr9pu/xUfZsmJsMTbybxqJI2nfus4afzAJ9neSMPsIfu2YMAeOJSSRDhwbWsee8zpJuruvI3w/GI/B3+rvPM7wmIN1WMLWWTIfljDbOkvQu2697zzp7sGNhEit8J3EaXPasTu1dVcppXqpt70RDwZGA+2tvXnAZyIygx7Of6P6hya+qgMRWQ+sC3msBy43xiyyNLB+1FxW1qtypXrKGEPFs+V4drWRe33BPie9wDeJ1z6tPDY4GBNo2d476Q5PytkrYY6crIcn3SE3D3p7cyD0hoDvmxsQxhOhdT7SjYSQ5/Rs1aXes0P25XnEH5JwgF5AKaWUMWY9kNG+LSI7gCONMVUi8jLwlIjcR2Byq7HAJ5YEqjTxVXs5AZgafMwnsK7vl8CwSXzjsrNpLt37ZlxcdrYF0aihpO79Gho/r2fEt9NxjnFZHc6AJyIgDPmxxcb/TYLfbWLfWYIeIbGvfb+G8sdLyLkmX3/elFKqj4jI08CJQJqIFAN3GWP+EunY4Fw3zxK4lvYCP9AZna0jpodrE6rhSUTGAj83xlxuZRwul8u43e5+ea3wMb4A9rg4pi5apF2d1T5r2dlM0f07cI2PJ/uqvCGfzCnr+dxeiu/fibfWS+4PCojNj7M6JKWUGvBEpMkYo3cLhyAd16k6CCa6exhjviLQ+jts5J11FlMXLSIuJwdEiMvJ0aRX7Rdfo5eyZcU4kqLIvDhHk17VL+wuB7nXFmBz2ildWkRbZavVISmllFKW0RZf1YGIvE1gkH4JgTG+sQRukFxjjGmyKq7+bPFVqi8Zv6H0kSKav2oi7+aR2uqm+l1bZSvF9+9EooS8m0YRlbz/axErpdRQpS2+Q5e2+KoOjDGzjTEFwAXAa8A2wElgprrNlgan1CBU/VYVTZvdpJ+bqUmvskR0Rgw51xTgb/ZT+lAhPrfX6pCUUkqpfqctvgoAERHTzQ+DiCQaY+r7K6ZQ2uKrBiP3lkZKHy4i4fDEQBfnQbI+rBqamra5KX24iOicGPKuH4ktRu99K6VUOG3xHbr0v55q97aI3CgiBaGFIhItIieJyGPAuRbFptSg46n1UPFEKdGZMWScn61Jr7Kcc4yLrMtzaS1uoezRYvzeA7WOklJKKTXwaOKr2p0B+ICnRaRURL4Uke3AV8CFwO+NMcusDFCpwcL4DOWPleD3GrKvzNWWNTVgxE9JIPOCbJq2uql4sjSwDJJSSik1DGhXZ7UXEYkC0oBmY0ytxeEA2tVZDS67Xqqg9t/VZF2WS8JhiVaHo9Reat7ZTdWqShKPTibj/CztkaCUUkHa1XnoclgdgBp4jDEeoMzqOJQajBq+qKf239UkH5eiSa8asFJOHIHP7aPmrd3YXXbSvp1hdUhKKaXUAaWJr1JK9ZG2ylYqV5QROzKWtDMzrQ5HqS6N+FZ6h+Q35cQRVoeklFJKHTCa+CqlVB/wt/kpW1YCDiHr8jzEoV1H1cAmImScl4W/yUfVqkrsTjuJM5KtDksppZQ6IDTxVR2ISAwwDxhFyM+HMeaXVsWk1EBnjKHy+XLaylvJWZBPVEqU1SEp1SNiEzIvycHXXEzFM2XYnHbipyRYHZZSSinV53SqURVuFXAW4AXcIQ+lVCfqP66lYXUdqael4ZoQb3U4SvWKzWEj53t5xOTFUv5YCU3b9E++UkqpoUdndVYdiMgGY8wUq+MIp7M6q4GqpbiF4j/uIO5gJzkL8hGbdnFWg5Ov0UvxAzvx1nnJ/cFIYvNirQ5JKaX6nc7qPHRpi68K96GIHGJ1EEoNBr5mH+XLirHH28m8JEeTXjWo2eMd5FxbgC3ORunDhbTtarM6JKWUUqrPaOKrws0CPhWRLSKyTkTWi8g6q4NSaqAxxlDxVCmeGg9Zl+fiiNcpE9TgF5UcRe61BWCg5P8K8dZ6rA5JKaWU6hPa1Vl1ICIjI5UbY3b2dyyhtKuzGmhq/rWbqlcqSTs7k5QTUq0OR6k+1VLUTMmDhTiSHeTdOAq7y251SEop1S+0q/PQpS2+qgNjzM5ID6vjUmogaf5vE1WvVRI/LYHk41OsDkepPhebH0f21Xl4dnsofaQQf6vf6pCUUkqp/aKJr9qLiEwTkRuCj2lWx6PUQOKt91L2WDFRI6LJmJ+NiI7rVUOTc4yLrMtyaSlsoeyvxRiv9hBTSik1eGniqzoQkZuB5UBG8PGkiNzYi/PPCI4P3iYit0fYf1Zw7PAXIrJGRGb1XfRKHVjGZyh/ogR/i5/sK3Kxx2r3TzW0xR+SQMYF2TRtcVP+VCnGr8mvUkqpwUnH+KoOghNZHW2McQe3XcB/jDFTe3CuHdgKnAoUA6uBC40xX4YcEw+4jTFGRKYCzxpjJnRXt47xVQNB1WuV1Ly1m8yLskmcnmx1OEr1m5q3d1P1ciVJxySTfl6W9nRQSg1ZOsZ36NJpSFU4AXwh275gWU/MALYZY74GEJEVwFnAnsTXGNMYcrwL0DsvalBo3NBAzVu7STw6WZNeNeykzB6Br9FHzb92Y493MGJOutUhKaWUUr2iia8K91fgYxFZSSDhPRt4tIfn5gJFIdvFwMzwg0TkHOAeAl2pv91ZZSKyAFgAEB0d3cMQlOp7nt1tVDxVSkxuDOnnZFodjlKWGPGddHxuL9VvVGFz2nU2c6WUUoOKJr6qA2PMfSLyDnAsgcT3cmPMFz08PVLL8F4tusaYlcBKETke+BVwSiexLAWWQqCrcw9jUKpP+T1+ypaVAJB9RR62KJ0aQQ1PIkLG+dn4mv1UvVSB3WkncXqS1WEppZRSPaKJrwJARN43xswSkQYCyaqE7DPGmMQeVFMM5Ids5wGlnR1sjHlXRA4WkTRjTNW+xq7UgbRrZQWtxS1kX5VHVJr2PFDDm9iFrEtzKF1aRMWKUmxxNuKnJFgdllJKKdUtbbpQABhjZgW/JhhjEoNf2x89SXohMJnVWBEZLSLRwHzg5dADRGSMBGdFEZHDgWhgd9+9E6X6Tv3qOur/U0vKSSP04l6pIJvDRs738ojJjaX88RKa/9tkdUhKKaVUtzTxVR2IyG96UhaJMcYL3AC8DmwiMGPzRhG5VkSuDR42D9ggIl8ADwIXGJ1aXA1ArWUtVD5fRtzBTkZ8SyfyUSqULdZO7oJ8HClRlP65iNaSFqtDUkoppbqkyxmpDkTkM2PM4WFl63qynNGBpMsZqf7kb/FR+Psd+Jt9FNx2EI5EHRWiVCSeGg/FS3ZgfIa8G0cRna7DAZRSg5suZzR0aYuvAkBErhOR9cB4EVkX8tgOrLc6PqX6izGGimfK8OxqI+uyXE16lepCVEoUudcWYPxQ8lAh3jqP1SEppZRSEWmLrwJARJKAFALLDN0esqvBGFNtTVTf0BZf1V9q361m18oKRnwnndST06wOR6lBoaWwmeI/FRKVGkXeD0Zid9mtDkkppfaJtvgOXdriqwAwxtQZY3YYYy4E6oFMYCQwJbjskFJDXvOOZna9XIFrcjwps0dYHY5Sg0ZsQRw5V+XhqWyj9M9F+Fv9VoeklFJKdaCJr+pARK4G3iUwQdX/BL/ebWVMSvUHX6OX8seKcSRFkXlRDmKLtCy1UqozzrEusi7LoWVnM2XLijFe7VGmlFJq4NDEV4W7GZgO7DTGzAYOA3ZZG5JSB5bxG8qfLMXX6CP7ilzsTu2mqdS+iJ+aSMZ3s2na7Kb8qVKMX5NfpZRSA4PO2qLCtRhjWkQEEYkxxmwWkfFWB6XUgVT9ZhVNW9xknJ9FbH6c1eEoNaglHZWMz+1j96uV7HLZST83k+Dy7UoppZRlNPFV4YpFJBl4CXhTRGqAUksjUuoAcm9upPr1KhKOTCLx6GSrw1FqSEg9eQR+t5eat6uxu+yMOEPXwlZKKWUtTXxVB8aYc4JP7xaRt4Ek4B8WhqTUAeOp8VD+ZCnRWTFknJelrVJK9aERczPwNfmofr0Ku9NO8vGpVoeklFJqGNPEV+0hgav+PGNMEYAx5t8Wh6TUAWO8hvLHS8BryL4iF1uMTnmgVF8SETLOz8bX5GPXygpsLjuJRyRZHZZSSqlhSq/01B4msKjzS1bHoVR/qHqlgpYdzWTMzyY6I8bqcJQaksQuZF2aS9wYJxVPleLe2GB1SEoppYYpTXxVuI9EZLrVQSh1IDV8UU/tuzUkH59CwqGJVoej1JBmi7KRfVUeMTmxlD1WQvPXTVaHpJRSahjSxFeFmw38R0T+KyLrRGS9iKyzOiil+kpbZSsVK8qIHRVH2txMq8NRaliwx9rJuSYfR3IUpY8U0VraYnVISimlhhlNfFW4DcDBwEnA3OBjs6URKdVH/K1+ypaVYHMIWZflIg6dzEqp/uKId5B7XQG2WBslDxXSVtVmdUhKKaWGEU18VbgxxpidIY8dwASrg1JqfxljqHy+nLbyVjIvySEqJcrqkJQadqJSosi9tgDjh9KHCvHWeawOSSml1DChia8CQESuE5H1wPhgF+f2x3ZAuzqrQa/+o1oa1tSReloargnxVoej1LAVnRlD7vfz8TZ4KXm4CF+Tz+qQlFJKDQMSmMhXDXcikgSkAPcAt4fsajDGVFsT1TdcLpdxu91Wh6EGqZaiZoqX7CTuYCc5C/IRm3ZxVspqTVvclD5SRExBLLnXFmCL1nvxSinriUiTMcZldRyq72niqwYFTXzVvvI1+Si8dzv4DQW3jsYer8uXKzVQNKytp/yxEpwTXORclY/Y9aaUUspamvgOXXoFqDoQkRhgHjCKkJ8PY8wvrYpJqX1l/IaKp0rx1nrIu3GUJr1KDTAJ0xLxn++j8tlyKp4qJfPiHO2RoZRS6oDQq0AVbhVQB3wKtFoci1L7pebtatwbG0k/J5O4UXFWh6OUiiDp6BR8bh+7X9uFzWkn/dxMRDT5VUop1bc08VXh8owxZ1gdhFL7q2mbm92vVRJ/aAJJx6VYHY5SqgspJ4/A5/ZR+0419ng7I05PtzokpZRSQ4wmvirchyJyiDFmvdWBKLWvvHUeyh8vISo9mswLsrX1SKkBTkRIOzMDX5OP6n9UYXfZSZ6VanVYSimlhhCdQlGFmwV8JiJbgssZrReRHi9nJCJnBM/dJiK3d3HcdBHxich5fRK1UkHGZyh/ohR/q5/sK3KxxdqtDkkp1QMiQuZ3s3FNiWfXixU0fFZndUhKKbUXEXlURCpFZENI2e9EZHPw2nmliCSH7PtZ8Lp4i4icbknQCtDEV+1tDjAGOA2YC3wn+LVbImIHHgzWMQm4UEQmdXLcb4DX+yhmpfbY/bddNP+3iYzzsonJjrU6HKVUL4hdyLosl7iDnJQvL8W9qdHqkJRSKtwyIHxY4JvAFGPMVGAr8DOA4HXwfGBy8Jw/Ba+DIxKRG0REx2cdIJr4qnCFwHHA5caYnYABMnt47gxgmzHma2NMG7ACOCvCcTcCLwCVfRCvUns0bmig5l+7STw6mcTpSVaHo5TaB7YoG9lX5xGTE0vZX4tp3t5kdUhKKbWHMeZdoDqs7A1jjDe4+RGQF3x+FrDCGNNqjNkObCNwvdyZLGC1iDwb7EWpY7X6kCa+KtyfgKOBC4PbDQRacXsiFygK2S4Olu0hIrnAOcBD+xemUh15qtqoeKqUmLxY0s/p6b0apdRAZI+1k7MgH0dyFKWPFNFa2mJ1SEqp4cMhImtCHgt6ef73gL8Hn3d7bRzKGPNzYCzwF+AK4CsR+X8icnAvY1ARaOKrws00xvwAaAEwxtQA0T08N9JdKRO2/Qfgp8YYX7eViSxo/6Pj9Xq7O1wNY36Pn7LHSgAC43qj9E+bUoOdI8FB7rUF2KJtlDxchKeqzeqQlFLDg9cYc2TIY2lPTxSRhYAXWN5eFOGw8GvjjjuNMUB58OEFUoDnReS3PY1DRaZXhyqcJzj2wACISDrg7+G5xUB+yHYeUBp2zJHAChHZAZxHYKzD2ZEqM8Ysbf+j43DoBOSqc7tWVtBa3ELmRTlEjejpfRql1EAXlRpFzrUFGK+h5OFCvPV6E1QpNTCJyOUE5sa5OJi8Qs+ujUPruElEPgV+C3wAHGKMuQ44Aph3QAIfRjTxVeGWACuBDBFZBLwP3NPDc1cDY0VktIhEExjM/3LoAcaY0caYUcaYUcDzwPXGmJf6Kng1/NSvrqX+P7WknDyC+CkJVoejlOpjMVkx5C7Ix1vvpeThQnzN3XYYUkqpfiUiZwA/Bc40xoROTPAyMF9EYkRkNIFuzJ90UVUacK4x5nRjzHPGGA+AMcZPIKlW+0Gb0VQHxpjlwTtNJxPonnG2MWZTD8/1isgNBGZrtgOPGmM2isi1wf06rlf1qdbSFiqfKydujJMRc9KtDkcpdYDEjowj+8o8Sv9cROkjRXu6QCulVH8TkaeBE4E0ESkG7iIwi3MM8GZwPqqPjDHXBq+DnwW+JNBt+QddDfczxtwZfI0MIDakvLCn1+Oqc/JNS7xSICKPATcbY2qD2ynAvcaY71kZl8vlMm6328oQ1ADja/FRdN8O/C0+Cm47CEei3sdTaqhr+Lye8idKcE6MJ+d7eYhdJzxVSvUtEWkyxrgseu25wH1ADoHVT0YCm4wxk62IZ6jR26Uq3NT2pBf2TG51mHXhKLU3YwyVK8rw7G4j+/I8TXqVGiYSDksk47wsmr5spOLpUoxfb94rpYaU/wWOArYaY0YT6IH5gbUhDR2a+KpwttCFs0UkFe0SrwaYuvdqaFzbwIhvZRB3sNPqcJRS/SjpmBRGfCudhk/rqXqpAu25ppQaQjzGmN0Ersdtxpi3gUMtjmnI0IRGhbsX+FBEnicws/N3gUXWhqTUN5p3NLFrVQWuKfGknJRqdThKKQuknDICn9tH7b+rscc7SD0tzeqQlFKqL9SKSDzwHrBcRCoJjA1WfUDH+Kq9iMgk4CQCk1v90xjzpcUh6RhfBYC30UvRvdvBJhTcNhp7nN3qkJRSFjF+Q8XTZTSsqSP9vCySj03p/iSllOqGxWN8XUAzgV65FwNJwPJgK7DaT9riq/YSTHQtT3aVCmX8hoonS/E1+si7eZQmvUoNc2ITMudn42/2seuFcuxOOwmHJVodllJK7Y8oYFLw+UvGmDorgxlqNPFVHYhIDIEFskcR8vNhjPmlVTEpBVD9RhVNW9xkXJBFbF5s9ycopYY8sQtZl+VS8nAh5ctLsMXZcE2ItzospZTqFRGJBpYCZwPbCfS6HCkiK4FrjTFtFoY3ZOjkVircKuAsAuMJ3CEPpSzj3txI9RtVJExPInFmstXhKKUGEFu0jZyr84nJiqHsr8U072i2OiSllOqtnxNo7c03xhxmjDkUKCDQCPULKwMbSnSMr+pARDYYY6ZYHUc4HeM7fHlqPBTeux1HooP8H47CFq3365RSe/M2eClesgNfk4+8G0YSk609Q5RSvWfFGF8R2QDMMMY0hZXHAx8NxGvzwUivIFW4D0XkEKuDUArAeA3ljxWD15B9Ra4mvUr1QPGqVbx13HG8MmYMbx13HMWrVlkdUr9wJDjIva4AibJR8lARnt3aM1ApNWj4w5NeAGNMI4FVVlQf0KtIFW4W8KmIbBGRdSKyXkTWWR2UGp6qXq6gZWcLGfOzic6IsTocpQa84lWrWLdwIc2lpWAMzaWlrFu4cNgkv1Gp0eRek4/x+il5qBBvg64CopQaFIyIpIhIavgD8Fsd3FChXZ1VByIyMlK5MWZnf8cSSrs6Dz8Nn9dT/ngJycenkn5OptXhKDUovHXccYGkN0xcTg6nvPeeBRFZo3lHEyX/V0h0ejS5Pxips8ArpXrMoq7OOwgkuBJhtzHGHNSf8QxV2uKrOggmuMnA3OAj2eqkVw0/bZWtVDxTRuyoONLmZlgdjlKDRnNZWa/Kh6q4UU6yr8yjtbyVsr8U42/TBhOl1MBljBlljDnIGDM6wkOT3j6iia/qQERuBpYDGcHHkyJyo7VRqeHE3+qn7K8l2BxC1uW5iCPSzU+lVCRx2dm9Kh/KXBPiybooh+avmyh/vATj0x5uSik1nGniq8JdBcw0xtxpjLkTOAr4vsUxqWHCGEPlc2W0VbSSeWkOUclRVoek1KAy4bbbsMfFdSizx8Ux4bbbLIrIWgmHJ5E+Lwv3xkYqninD+DX5VUqp4cphdQBqwBHAF7LtI/J4A6X6XP1/amn4tJ7UM9JwjY+3OhylBp28s84CYPPixTSXlRGXnc2E227bUz4cJR+bgt/tY/ffd2F32kk7KwMR/bemlFLDjSa+KtxfgY9FZGVw+2zgL9aFo4aLlqJmdr1YgXOCi9RT06wOR6lBK++ss4Z1ohtJyqkj8Lm91P67GrvLrn9jlFIDjojYgHW6Zu+Bo4mv6sAYc5+IvENgWSMBrjTGfG5tVGqo8zX5KFtWgj3BTtbFOYhNW2OUUn1HREg7KxOf28fuv+3C7rKTdEyK1WEppdQexhi/iKwVkQJjTKHV8QxFmvgqAERkDJBpjPnAGPMZ8Fmw/DgROdgY819rI1RDlfEbKpaX4q3zkH/jKOzx+mdJKdX3xCZkXpiDr9lP5fPl2Jx2Eg5NtDospZQKlQ1sFJFPgD3reBpjzrQupKFDrzBVuz8Ad0Qobw7um9ufwajho+Zfu3F/2Uj6uZnEjozr/gSllNpHYheyL8+l5KFCyp8swRZn0/kElFIDyf9YHcBQJsboDIcKRGRDZ2MKRGS9MeaQ/o4plMvlMm63u/sD1aDStM1NyZ8KiT80kaxLc3TCGaVUv/A1+yh+YCeeqjbyrh+pN92UUnuISJMxxmV1HKrv6XJGql1sF/v0ikD1OW+dh/LHS4hKjybzu1ma9Cql+o09zk7uNQU4Eh2ULC2itbzV6pCUUgoROUpEVotIo4i0iYhPROqtjmuo0MRXtVstInut1ysiVwGfWhCPGsKMz1D+RCn+Vj/ZV+Rhi7VbHZJSaphxJDrIvbYAcQilDxXiqfZYHZJSSj0AXAh8RaDh6epgmeoDmviqdj8ErhSRd0Tk3uDj3wR+4W7uaSUicoaIbBGRbSJye4T9J4pInYh8EXzc2XdvQQ0Wu/+2i+b/NpHx3WxismOsDkcpNUxFjYgm95p8/G1+Sh4qxNvgtTokpdQwZ4zZBtiNMT5jzF+BEy0OacjQxFcBYIypMMYcQ2BQ/Y7g43+MMUcbY8p7UoeI2IEHgTnAJOBCEZkU4dD3jDGHBh+/7JM3oAaNxvUN1PxrN0nHJJN4RJLV4Sg15CxfDqNGgc0W+Lp8udURDWwxObHkfD8fb62H0ocL8bX4rA5JKTV8NYlINPCFiPxWRH4E6HjjPqKJr+rAGPO2Meb+4ONfvTx9BrDNGPO1MaYNWAGc1fdRqsHKU9VGxVOlxOTFknZ2ptXhKDXkLF8OCxbAzp1gTODrggWa/HYnbrST7CvzaC1rpezPxfg9fqtDUkoNT5cSyM9uILCcUT4wz9KIhhBNfFVfygWKQraLg2Xhjg4u0P13EZncP6Epq/k9fsqWFYMNsq/MxRalf36U6msLF0JTU8eypqZAueqaa2I8WRfn0Px1E+WPl2B8uuqFUqp/GWN2AgJkG2P+xxhzS7Drs+oDeuWp+lKkaXnDrxw+A0YaY6YB9wMvdVqZyAIRWSMia7xeHXc12O16sYLWklYyL8ohKjXa6nCUGpIKC3tXrjpKODyJ9HMycW9opOLZMnTJR6VUfxKRucAXwD+C24eKyMuWBjWEOKwOQA0sIhJDoEvFKEJ+Pno4FreYQJeMdnlAaegBxpj6kOd/E5E/iUiaMaYqvDJjzFJgKQTW8e3F21ADTP0ntdR/VEvKKSOIn5xgdThKDVkFBYHuzZHKVc8kH5eKz+2j+vUq7E47aWdm6HJrSqn+cjeBoYPvABhjvhCRURbGM6Roi68Kt4rAuFwvgbEF7Y+eWA2MFZHRwYH584EOd6lEJEuCVxAiMoPAz+DuPopdDUCtpS1UPl9O3BgnI85ItzocpYa0RYvA6exY5nQGylXPpZ6eRtJxKdS+U03NP/VflFKq33iNMXVWBzFUaYuvCpdnjDljX040xnhF5AbgdcAOPGqM2Sgi1wb3PwScB1wnIl6gGZhvtC/ZkOVr8VG2rARbnJ2sS3MRu7aaKHUgXXxx4OvChYHuzQUFgaS3vVz1jIiQfnYmfreP3a/twu6yk3R0itVhKaWGKBH5G/ADYIOIXATYRWQscBPwoaXBDSGiOYcKJSJLgfuNMeutjiWUy+UybndPG57VQGCMofyxEhrXN5B3/UjiDnZ2f5JSSg0gxmco/UsRTZvdZF2WS8KhiVaHpJQ6wESkyRjTr0sIich3gf8FngDigFODu14HfmWMae3PeIYq7eqsws0CPhWRLSKyTkTWi8g6q4NSg0/tuzU0rm0g7TsZmvQq1Z+2L4eXRsFTtsDX7bqW0b4Su5B9RR6xo+KoeLKUpi16A1Yp1feMMc8ChwHxwLeBZwgsC1pDoCVY9QHt6qzCzbE6ADX4NW9vourlClyHxJN8YqrV4Sg1fGxfDp8sAF9wTaOmnYFtgNHa33lf2KJt5FydT/EDOyl9tIi860cSOzLO6rCUUkOPh8C8OjEEEmDtltvHtKuz2ouITAOOC26+Z4xZa2U8oF2dBxNvo5eixduRKCH/ltHY4+xWh6TU8PHSqECyG845Es7e0d/RDCneOg9FS3bib/WTf+NIojNjrA5JKXUAWNTV+QzgPgKTwv7SGNPUzSlqH2hXZ9WBiNwMLAcygo8nReRGa6NSg4XxG8qfKMXn9pF9RZ4mvUr1t6ZOFuztrFz1mCMpitzrChAblDxUiKfGY3VISqmhYyFwvjHmdk16DxxNfFW4q4CZxpg7jTF3AkcB37c4JjVIVL9eRfNWN+nzsojJjbU6HKWGH2cnC/Z2Vq56JTotmtxrC/C3+Cl5qBBvo9fqkJRSQ4Ax5jhjzEar4xjqNPFV4QTwhWz7gmVKdcm9qZHqN6tImJFE4swkq8NRaniatgjsYZPJ2Z2BctUnYnJiyfl+Pt4aD6UPF+Fr8XV/klJKKctp4qvC/RX4WETuFpG7gY+Av1gbkhroPDUeypeXEp0dQ8a8LET0XolSlhh9McxYGhjTiwS+zliqE1v1sbiDnGRfkUdraQtlfynG7/FbHZJSSqlu6ORWai8icjiBZY0EeNcY87nFIenkVgOY8RqKH9hBW3kb+beOJjo92uqQlFKqX9R/WkfFk6W4Dokn+/I8xK43/ZQa7KyY3Er1D13OSHUgIkcYYz4FPgspm2uMecXCsNQAtuvlClp2tpB1Ra4mvUqpYSXxiCT8bh+7VlZQ+VwZGRdka48XpZQaoLSrswr3iIgc0r4hIhcCP7cwHjWANXxeT917NSSfkErCtESrw1FKqX6XfHwqqaelUf9xHbtf3WV1OEoppTqhLb4q3HnA8yJyMYHuzpcBp1kbkhqI2ipaqXimjNhRcaTNzbA6HKWUskzqGWn4mnzU/Gs3Nqed1JNHWB2SUkqpMJr4qg6MMV+LyHzgJaAIOM0Y02xtVGqg8bf6KftrMbYoIfvyXB3XppQa1kSE9HMy8TX52P1qJXaXnaSjkq0OSymlVAhNfBUAIrIeCJ3pLBWwE5jhGWPMVGsiUwONMYbK58poq2wj95oCHMlRVoeklFKWE5uQdWEOpU0+Kp8tw+60ET9Vh4AopdRAobM6KwBEZGRX+40xO/srlkh0VueBo/aDGnY9X86IOemknpZmdThKKTWg+Fv9lDxUSGtRCznX5OMcq5PDKjWY6KzOQ5cmvmpQ0MR3YGgpbKZ4yU7ixjnJuTofsWkXZ6WUCudz+yh+cCeeag951xcQWxBndUhKqR7SxHfo0sRXdSAiMcA8YBQhXeGNMb+0KibQxHcg8Ll9FN67HYyh4LbR2F06UkIppTrjrfNQtGQnptVP3o0jic6MsTokpVQPaOI7dOlyRircKuAswAu4Qx5qGDN+Q8VTpXjrPWRfkadJr1JKdcORFEXutQVgg5KHCvHUeKwOSSnVB0TkURGpFJENIWWpIvKmiHwV/JoSsu9nIrJNRLaIyOnWRK1AW3xVGBHZYIyZYnUc4bTF11rVb1Wx+7VdpM/LJHlWqtXhKKXUoNFa0kLxAzuxJzrIv3Ek9ni9cahUV/xeP+6NjUSnRxOTE9vvr99di6+IHA80Ao+3XzOLyG+BamPMr0XkdiDFGPNTEZkEPA3MAHKAt4BxxhjfAX8jai/a4qvCfSgih1gdhBo4mr5ys/tvu4g/LJGkY1O6P0EppdQeMbmx5Fydj7fGQ8nSIvwter2rVDhjDC07m6l8voztd31F+bIS6j+utTqsiIwx7wLVYcVnAY8Fnz8GnB1SvsIY02qM2Q5sI5AEKwvobUcVbhZwhYhsB1oBAYwuZzQ8ees8lD9eQlR6NJkXZCOik1kppVRvxR3sJOvyXMoeLab00WJyFuRjc2jbg1KeGg8Na+qoX1OHp7INiRLiD0kgYXoSznGDaphtpjGmDMAYUyYiGcHyXOCjkOOKg2XKApr4qnBzrA5ADQzGZyh7vAR/m5/cH4zEFqMXaUopta/iJyeQOT+HiqdKKX+ilOzLc3VmfDUs+Vv9NK6rp351Hc3bmsAEbg6lnDSC+GkJ2GPtVofoEJE1IdtLjTFL97GuSL/kOs7UIpr4qg6MMTuDA/LHAqEDKyxdx1f1v92vVdLydTOZl+QQk6WzkSql1P5KnJ6Er8lH1UsVVD5XTsZ3s7QnjRoWjN/QvK2J+tV1NK6rx7QZotKiSD09jcQjkohKi7Y6xFBeY8yRvTynQkSyg6292UBlsLwYyA85Lg8o7YsgVe9p4qs6EJGrgZsJ/GJ+ARwF/Ac4qYfnnwH8EbADfzbG/DrCMScCfwCigCpjzAn7H7nqS43rG6h5u5qkY5NJPCLJ6nCUUmrISDkhFb/bS/Wbu7G77KR9J6P7k5QapNoqW6lfXUfDmjq8tV5ssTYSDk8icXoSsaPjhtKNn5eBy4FfB7+uCil/SkTuIzC51VjgE0siVJr4qr3cDEwHPjLGzBaRCcD/9OREEbEDDwKnErjDtVpEXjbGfBlyTDLwJ+AMY0xhyBgINUC0VbVR8VQpMfmxpJ2daXU4Sik15KTOScfn9lHzz0DymzJ7hNUhKdVnfG4fDZ8Hkt2WnS0g4JzgIu3MTFyT47FFD+6hUyLyNHAikCYixcBdBBLeZ0XkKqAQOB/AGLNRRJ4FviSwVOgPdEZn62jiq8K1GGNaRAQRiTHGbBaR8T08dwawzRjzNYCIrCAwm92XIcdcBLxojCkEMMZU7lWLsoy/zU/5smKwQfYVuTr5ilJKHQAiQvq8LHzNfqpersTmtJM0M9nqsJTaZ8ZncG9qpGF1He6NjRifITo7hrQzM0g4PBFHUpTVIfYZY8yFnew6uZPjFwGLDlxEqqc08VXhioOtsi8Bb4pIDT0fi5ALFIXWBcwMO2YcECUi7wAJwB+NMY/vT8Cq7+xaWUFrSSs5V+cRlTqgxtsopdSQIjYh66IcSpt8VD5Tht1pJ/6QBKvDUqrHjDG0FrfQsKaOhs/q8TX6sMfbSTo2hcQZSUTnxAylrsxqCNDEV3VgjDkn+PRuEXkbSAL+0cPTezJznQM4gsBdsTjgPyLykTFm616ViSwAFgBER2sSdqDVf1JL/Ue1pJw6AtdkvfhSSqkDTRxC9pV5lPxfIeWPl5CzIB/n2EG1hIsahrx1Hho+rad+TR1tZa2IXXBNiSdhehKuCfGIXZNdNTBp4qs6ZYz5dy9P6cnMdcUEJrRyA24ReReYBuyV+Aanjl8K4HK5dOr3A6i1pIXK58uJG+tkxBnpVoejlFLDhi3GRs738yl+YCdlfykm9wcFxObHWR2WUh342/y4NzRQv7qOpi1uMBA7Ko7087JIOCwRu9PyJYiU6pYYo/mEAhFp4JvW2fZbdSb43BhjEntQh4NAAnsyUAKsBi4yxmwMOWYi8ABwOhBNYGa7+caYDV3V7XK5jNvt7tV7Uj3ja/ZRdN92/G2GgttG40jQ+2FKKdXfvLUeipbsxLT5ybtpJNEZuoycspYxhpavm6lfXUvj2gb8LX4cKQ4Sjkwi8cikIfszKiJNxhjtejEE6RWuAsAYs999W40xXhG5AXidwHJGjwZns7s2uP8hY8wmEfkHsA7wE1jyqMukVx04xhgqV5ThqfaQd/1ITXqVUsoijuQocq8roHjJDkoeKiTvplFEJQ+dCYHU4OGpaqN+TR31q+vwVnuQaCH+0EQSj0wi7mAnYtOuzGpw0hZf1YGIxALXA7MItPi+BzxkjGmxMi5t8T0wat7ZTdWqStLOzNDlNJRSagBoKW6h5MGdOJIc5N04ErtLb0iqA8/X7KNxbT31n9TRsr0ZBOLGukg8Mon4qQnYYobPKg/a4jt0aeKrOgiuNdYAPBksuhBIMcacb11UmvgeCM1fN1H84E5ck+PJvjJPZ17sR8uXw8KFUFgIBQWwaBFcfLHVUSmlBorm/zZR8nAh0dkx5F0/clglHar/GJ+haaub+tV1uDc0YDyGqIxoEqcnkXBEElEpw7PHgSa+Q5cmvqoDEVlrjJnWXVl/08S3b3kbvBTdux2JEvJvGY09Tiel6C/Ll8OCBdDU9E2Z0wlLl2ryq5T6RuOGBsr+WkzcGBc538/TddVVn2ktbaF+TR0Na+rwNfiwOe0kHJ5I4vQkYvJjh/2NcE18hy5NfFUHIrKMQNfmj4LbM4HLjTHXWxmXJr59x/gNJQ8V0rKjmfybRxGTG2t1SMPKqFGwc+fe5SNHwo4d/R2NUmogq19dS8VTZcRPSyDrslwdW6n2mbfBS8Nn9TSsrqW1pBVs4JoUT+L0JFyTEhCH/my108R36NLEV3UgIpuA8UBhsKgA2ERgIipjjJlqRVya+Pad3X/fRfUbVWTMzyZpZrLV4Qw7NhvMP3o5/++7CylIK6SwqoA7nl3Eiv9cjN9vdXRKqYGmfS6GxKOTyTg/a9i3xqme83v9uDc00rCmDvemRvBDTF5soCvz4YnY43X8eCSa+A5d+hOvwp1hdQDqwHFvaqT6jSoSZyRp0muRG+Yu556zF+CKCfR1HpW+k0euXkBaGoD2dVZKdZRy4gh8bh81b+3G7rKT9u0Mq0NSA5gxhpadLTSsqaXh83r8TX7sSQ5SThxBwpFJxGQPzSWIlOoJbfFVexGRacBxwc33jDFrrYwHtMW3L3iqPRTeux1HsoP8m0dhi9bxYlZoXD6KeNm7r3OjGUn8xTv6PyCl1IBnjKHyuXLq/1NL2lkZpJyos/Crjjw1HhqCSxB5drUhUUL8IQkkTE/COc6l3eR7QVt8hy5t8VUdiMjNwPeBF4NFT4rIUmPM/RaGpfaT3+un7LFi8Buyr8jTpNdC8VLYq3KllBIRMs7Lwt/ko2pVJXanncQZyVaHpSzmb/UHliBaXUfzf5vAQNzBTlJOHkH8tATssTpxpVKhNPFV4a4CZhpj3AAi8hvgP4AmvoNY1apKWgtbyL4yl+j0aKvDGd6cBdAUYXYrZ0H/x6KUGjTEJmRekoO/uZiKZ8qwOe3ET0mwOizVz4zf0LytifrVdTSuq8e0GaLSokg9I43EI5KIGqH/45XqjCa+KpwAvpBtX7BMDVINn9VR934NySemEj810epw1LRF8MkC8IWsZ2R3BsqVUqoLNoeN7O/lUfynnZQ/VkLONfk4x2iPzOGgrbKV+tWBJYi8tV5ssTYSjkgi8cgkYkfH6aRnSvWAJr4q3F+Bj0VkJYGE9yzgL9aGpPZVW0UrFc+UETs6jrTv6IQoA8Lo4ARWaxdCU2GgpXfaom/KlVKqC7YYG7kL8im+fydlfy4m94aRxObpsnRDkc/to+HzwLjd1sIWsIFzvIu0MzNxTY7XYUtK9ZJObqX2IiKHA7OCm+8ZYz63Mh7Qya32hb/VT9Hvt+Nz+yi4dTSO5CirQ1JKKdVHPLUeipfswHgMeTeOJDpDZ+sdCozP4N7USP3qOtwbG8AH0TkxwSWIknAkapvVgaaTWw1d+tujIvEBJvjQlUUHocAMoGW0VbaRe22BJr1KKTXERCVHkXttAcX376TkoSLybxqpf+sHKWMMrcUtNKyuo+GzenxuH/Z4O8mzUkmcnkRMrrboK9UXtMVXdRAyq/MLBLo6nwNYPquztvj2Tu0HNex6vpwR30on9dQ0q8NRSil1gLQUNVPyYCGOZAd5N47C7tKZfAcLb52Hhk8DszK3lbcidsE1JZ7E6Uk4J8Qjdh23awVt8R26NPFVHYjIOuDokFmdXcB/jDFTrYxLE9+eaylspnjJTuLGOcm5Ol/X7lNKqSGuaZub0oeLiMmNIfe6kdhidOznQOVv8+Pe0ED96jqatrjBQOyoOBKnJxF/aCJ2p964sJomvkOXdnVW4XRW50HM5/ZRtqwEe6KdrItzNOlVSqlhwDnGRdZluZT9tZiyvxYHbno69O//QGH8hpbtzdSvrqXxiwb8rX4cKQ5STxlBwvRkXWZQqX6iia8KFzqrM8DZwKPWhaN6yvgN5ctL8NZ7yL9pFHaX/norpdRwEX9IAhkXZFO5oozyp0rJukRvflqtraqNhtV11K+pw1vtQWJsxE9LIHF6EnEHOfX7o1Q/0ytj1YEx5j4ReYfArM4CXDkQZnVW3av5526aNrlJn5dJbEGc1eEopZTqZ0kzk/E3+ah6uZJdcTbSz8vS9V37ma/ZR+MXgXG7LdubQcA51sWIOenEH5Kg3dCVspAmvqoDEfkncK8xZklI2VJjzAILw1LdaPrKze6/7yL+8ESSjk2xOhyllFIWSZk9Ap/bR80/d2N32RnxLV3D/UAzPkPTVndgCaINDRiPITozmhHfSSfhiCSidLZtpQYETXxVuNHAT0VkujHmf4JlR1oZkOqat9ZD+eMlRGdEk/ndbL27r5RSw9yIb6fjc/uofnM3NpeDlBNSrQ5pSGotbaF+dR0Nn9bha/Bhc9lJnJkcWIIoP1b/Hys1wGjiq8LVAicDS0TkFeASa8NRXTE+Q9njJfjb/OTdoDN5KqWUAhEh4/wsfE0+ql6qwO60kzg9yeqwhgRvg5eGz+ppWF1La0kr2ME1KZ7E6cm4JsbrpGJKDWCa+KpwYozxAteLyBXA+4D2nR2gql6rpGV7M1mX5hCdGWN1OEoppQYIsQlZl+ZQurSIihWl2OJsxE9JsDqsQcnv9ePe0EjD6jrcmxvBDzH5saSfm0nCYYnY4/VyWqnBQH9TVbiH2p8YY5aJyHrgBxbGozrRuK6e2rerSZqVQsLheidfKaVURzaHjZzv5VH8f4WUP15C7jUFxB3stDqsQcEYQ8vOFhpW19LwRT3+Jj/2JAcpJ44gYXoSMVl6s1mpwUaMMVbHoAYYEZkGHBfcfM8Ys7YX554B/BGwA382xvw6bP+PgYuDmw5gIpBujKnuql6Xy2XcbndPwxjy2na1UXTfdqIyosm7cSQ2h3ZxVkopFZmv0UvR/Tvx1XvJu2EkMbmxVoc0YHlqPDSsqaN+dR2eXW1IlBA/NYGE6Uk4x7p0CaJhQESajDEuq+NQfU8TX9WBiNwELABeDBadAyw1xtzfg3PtwFbgVKAYWA1caIz5spPj5wI/Msac1F3dmvh+w9/mp+iPO/DWeii49SCiUnW2SKWUUl3z1HgoXrID4zPk3TiK6PRoq0MaMPytfhrXBpYgat7WBEDcwU4SpieRMC0BW6zd4giHl+JVq9i8eDHNZWXEZWcz4bbbyDvrrH57fU18hy5NfFUHIrIOONoY4w5uu4D/GGOm9uDco4G7jTGnB7d/BmCMuaeT458C3jbGPNJd3Zr4fqNiRSn1H9eR8/18XJPirQ5HKaXUINFW0Urx/TuRGBv5N43EkTR8b5wav6H5qybq19TRuK4e02aISosiYXoSiUcmEZWqNwasULxqFesWLsTX3LynzB4Xx9RFi/ot+dXEd+jSMb4qnAC+kG1fsKwncoGikO1iYGbEFxFxAmcAN+xDjMNW3ce11H9cR+qpIzTpVUop1SvRmTHkLMin+E+FlDxcRN4PRmJ3Da/WzLaKVurX1NGwpg5vrRdbrI2EI5JInJ5E7Kg4XYLIYpsXL+6Q9AL4mpvZvHhxv7b6qqFJE18V7q/AxyKyMrh9NvCXHp4b6b9FZ10K5gIfdDW2V0QWEOh2TXS03nltLWlh1wvlxI11knpGutXhKKWUGoRiC+LIuSqP0oeLKP1zEbnXFgz5pfB8bi8Nnwe6MrcWtoANnBPiSTszCdeUeGxRQ/v9DybNZWW9KleqNzTxVR0YY+4TkXeAWQQS2SuNMZ/38PRiID9kOw8o7eTY+cDT3cSyFFgKga7OPYxhSPI1+yhbVozNaSfr0lydXEMppdQ+c451kXVZDmXLSihbVkzOVflDbv1Z4zW4NzVSv6YO98YG8EF0TgxpZ2WQcHgSjkS9BB6I4rKzaS7d+9IxLjvbgmjUUKNjfNUeEujfk2eMKer24MjnOwhMbnUyUEJgcquLjDEbw45LArYD+e1jibsznMf4GmMoW1aCe0MDeT8YSdxBuhSFUkqp/Vf3cS2VK8qIPyyRrEtyBv1NVWMMrcUt1K+uo/GzenxuH/YEe6Ar85FJOpv1IKBjfNWBpLe71B7GGCMiLwFH7OP5XhG5AXidwHJGjxpjNorItcH97WsEnwO80dOkd7ir/Xc17nUNpJ2VoUmvUkqpPpM0Mxm/20fVK5XsctlJPzdzUI5x9dZ5qF9TT8OaOtrKWxGH4JoST+L0ZJzjXYh98L2n4ao9ubVyVmc1dGmLr+pARB4ElhljVlsdS6jh2uLb/HUTxQ/uxDUlgewrcgflBYlSSqmBreqVSmr+tZvU09IYMWdwzCHhb/PTuL6BhtV1NG11g4HYUXEkTk8i/tBE7M7hNWmX6jva4jt0aYuvCjcbuEZEdgJuAuN8TU+WM1J9y9vgpezxEqJSo8icn61Jr1JKqQNixHfS8bm9VL9Rhd1lJ/n4VKtDisj4DS3bm6lfXUvjFw34W/04UqJIPTWNhCOTdG1ipVSXNPFV4eZYHYAK/HMvf6IEf5OP3JtHYY/TO9dKKaUODBEh4/xsfE1+dq2swOayk3hEUucnbF8OaxdCUyE4C2DaIhh98QGLr62qjYbVddSvqcNb7UFibCRMSyBhehJxBzkH/dhk1dHy5bBwIRQWQkEBLFoEFx+4Hy81jGhXZ9WBiDwG3GyMqQ1upwD3GmO+Z2Vcw62r8+6/VVL95m4y5meTNDPZ6nCUUkoNA36Pn9KlRTR/3UTO9/JwTU7Y+6Dty+GTBeBr+qbM7oQZS/s0+fU1+2j8IrAEUcv2ZpDAbNQJM5KIPyQBW7QuQTQULV8OCxZAU8iPl9MJS5f2X/KrXZ2HLk18VQci8rkx5rDuyvrbcEp83V82UvpIEYkzk8icn2N1OEoppYYRX4uPkgcLaatoJffagr0nVXxpFDTt3PtE50g4e8d+vbbxGZq2uANLEK1vwHgN0ZnRJExPIvGIJBzJUftVvxr4Ro2CnRF+vEaOhB07+icGTXyHLu3qrMLZRCTFGFMDICKp6M9Jv/FUeyhfXkJ0Tgzp52ZZHY5SSqlhxh5rJ+eafIrv30npI0Xk3TiSmJyQZYCaCiOf2Fl5D7SWBpYgavi0Dl+DL9DV+ujkwBJE+bE6x8UwUlgIFx6znP/33YUUpBVSWFXAHc8uYsV/tK+z2n+a0Khw9wIfisjzgAG+CyyyNqThwe/1U/ZYMfgh+4o87callFLKEo54B7nXFlC8ZAclDxWSd9MootOCE0c5Czpp8S3o1Wt4G7w0fFZPw+paWktawQ6uSQkkTk/CNTEecWiyOxzdMHc595y9AFdMoK/zqPSdPHL1AtLSADT5VftHuzqrvYjIZAKzOwvwT2PMlxaHNCy6Ole+UE7d+zVkX5lL/NREq8NRSik1zLVVtFJ0/07ssTbybhyJIylqv8b4+j1+3BsbaVhdh3tzI/ghpiCWxCOTSDgsEXu8tscMd43LRxEve99YaTQjib94R7/EoF2dhy5NfNWgMNQT3/pP66h4spTk2amkn5lpdThKKaUUAC2FzRQ/uJOoEdHk3TAysD5uL2Z1NsbQsrOZ+k/qaPyiHn+zH0eSg4Qjk0g4MomYrJh+fkdqQHvKRqDDYTiBi/z9EoImvkOXJr4KABF53xgzS0Qa6PgXp30dX0ubIIdy4tta3krR77cTkxtL3g9GInbt3qWUUmrgaNripvSRImLyY8m9rqBHQ3E81R4a1gSWIPLsakOihfhDEkicnkzcWF2CSHXiAE6e1lOa+A5dmviqQWGoJr7+Vj9Fv9+Oz+2j4LbRgW5kSiml1ADTsLae8sdKcE5w8U5cPgt/IXuts+pv8dG4roH61XU0bwt0hY4b4yRxehLxUxOwxeqa9Kob/bRcVlc08R26NPFVAIjIy13tN8ac2V+xRDIUE19jDOVPltL4eT251xXgHKt/Y5VSSg1cdf+p4c+/bOIX/8qmue2bVt+4WMPiK2o4LbES02aISo8OjNs9MomoVL2hq3qpF13pDwRNfIcuTXwVACKyCygCngY+JtDFeQ9jzL+tiKvdUEx8a9+vZtcLFYz4Vjqpp6ZZHY5SSinVrfxMH8WVe7fc5iR6+OyRKhJnJBE7Mk6XIFKDVk8SXxH5EXA1geGB64ErASfwDDAK2AF8t315UDUwaOKrABARO3AqcCEwFXgNeNoYs9HSwIKGWuLbsrOZovt34BwfT85VeTrWSSml1KBgsxmM2ft/lojB79f/ZWrw6y7xFZFc4H1gkjGmWUSeBf4GTAKqjTG/FpHbgRRjzE/7J2rVE7pQqALAGOMzxvzDGHM5cBSwDXhHRG60OLQhx+f2UvZYMY7EKLIuytGkVyml1KBRUBD5f1Zn5UoNUQ4gTkQcBFp6S4GzgMeC+x8DzrYmNNUZTXzVHiISIyLnAk8CPwCWAC9aG9XQYvyG8uWl+Op9ZF+Ri92lE30opZQaPBYtAqezY5nTGShXajgwxpQAi4FCoAyoM8a8AWQaY8qCx5QBGdZFqSLRlcIVACLyGDAF+DvwP8aYDRaHNCTV/HM3TZvcpJ+XRWxBnNXhKKWUUr1ycXCOoYUL2WtWZ6WGCIeIrAnZXmqMWdq+ISIpBFp3RwO1wHMickn/hqj2hY7xVQCIiB9oH0Sr6/geAE1b3ZQ8VEjC4YlkXpyjE38opZRSSg0wPRjjez5whjHmquD2ZQSGCZ4MnGiMKRORbOAdY8z4fgla9Yi2+CoAjDHa7f0A8tZ6KH+ihOiMaDLOz9akVymllFJqcCoEjhIRJ9BMIOFdQ6AB6XLg18GvqyyLUEWkia9SB5jxGcoeL8Hf5ifvhpHYYvQeg1JKKaXUYGSM+VhEngc+A7zA58BSIB54VkSuIpAcn29dlCoS7eqsBoXB3NV516oKat+pJuvSHBIOT7I6HKWUUkop1YmerOOrBidtelLqAGpcV0/tO9UkzUrRpFcppZRSSimLaOKr1AHStquNiqfLiCmIJe0sndFeKaWUUkopq2jiq/qUiJwhIltEZJuI3B5hf5KIvCIia0Vko4hcaUWcB5q/zU/ZsmKwCdmX52Fz6K+aUkoppZRSVtGrcdVnRMQOPAjMASYBF4rIpLDDfgB8aYyZBpwI3Csi0f0aaD/Y9UI5bWWtZF2SQ1RqlNXhKKWUUkopNaxp4qv60gxgmzHma2NMG7CCwALfoQyQIIH1fOKBagIz4g0ZdR/XUv9JHamnpuGaGG91OEoppZRSSg17mviqvpQLFIVsFwfLQj0ATARKgfXAzcYYf/+Ed+C1lrSw64Vy4sa5SD09zepwlFJKKaWUUmjiq/qWRCgLXy/rdOALIAc4FHhARBIjViayQETWiMgar3fgNwr7mn2ULSvG7rSTdWkOYov0cSillFJKKaX6mya+qi8VA/kh23kEWnZDXQm8aAK2AduBCZEqM8YsNcYcaYw50uFwHJCA+4oxhoqnS/FUe8i6LBdH/MCOVymllFJKqeFEE1/Vl1YDY0VkdHDCqvnAy2HHFAInA4hIJjAe+LpfozwAat+pxr2+kbS5GcQd5LQ6HKWUUkoppVQITXxVnzHGeIEbgNeBTcCzxpiNInKtiFwbPOxXwDEish74J/BTY0yVNRF3YftyeGkUPGULfN2+vNNDm79uourVSuKnJpB8Qmq/haiUUkoppZTqGTEmfAimUgOPy+Uybre7f15s+3L4ZAH4mr4pszthxlIYfXGHQ70NXgoXb8cWYyP/llHYY+39E6NSSimllOpzItJkjHFZHYfqe9riq1S4tQs7Jr0Q2F67sEOR8RvKHy/B3+wj+4pcTXqVUkoppZQaoDTxVSpcU2GPynf/YxfN25rIOC+LmJzYfghMKaWUUkoptS808VUqnLOg23L3xgZq3txN4lHJJM5I7p+4lFJKKaWUUvtEE1+lwk1bFBjTG8ruDJQDnuo2yp8qJSY3hvRzMi0IUCmllFJKKdUbmvgqFW70xYGJrJwjAQl8DU5s5ff6KVtWAn7IuiIPW7T+CimllFJKKTXQ6azOalDo11mdu1D5fBl1H9SS/b084g9JsDocpZRSSinVh3RW56FLm6uU6qH6T+uo+6CWlNmpmvQqpZRSSik1iGjiq1QPtJa3UvlsGbEHxTHi2xlWh6OUUkoppZTqBU18leqGv8VH2V+LscXYyL4sF7GL1SEppZRSSimlekETX6UiWL4cRo0Cm81QkGd44d1Ysi7NxZEUZXVoSiml/n979x96V13Hcfz5cl+ltqyppWi5jcAImWwzKYoCIYqKIkGyxpBZf0iFYYXQD5JWIoVE9If0x5ckzMx0mJgFRoVi9kt0iTrnj6wpzGFuFulMUr/v/jhn8O1LuOb33B/n3OcDLvd7z7073/cH3vvc+/qecz5XkqTDZPCVlrj6ajj/fHj0UagKe/bPcfEtJ3HDHa5zIEmSJPWRqzqrF8a5qvO6dU3oXWrtWti9eywlSJIkaQJc1Xm4DL7qhXEG3yOOgP/13yKBhYWxlCBJkqQJMPgOl6c6S0usWXN42yVJkiRNN4OvtMSll8LKlf+9beXKZrskSZKk/jH4Skts2QLz8801vUlzPz/fbJckSZLUP17jq14Y5zW+kiRJmk1e4ztcHvGVJEmSJA2awVeSJEmSNGgGX0mSJEnSoBl8JUmSJEmDZvCVJEmSJA2awVeSJEmSNGgGX0mSJEnSoBl8JUmSJEmDlqqadA3SISVZAP41gV89B7wwgd+r2WB/aZTsL42aPaZRmlR/vbKqPDg4QAZf6SUkubOqzph0HRom+0ujZH9p1OwxjZL9pa751wxJkiRJ0qAZfCVJkiRJg2bwlV7a/KQL0KDZXxol+0ujZo9plOwvdcprfCVJkiRJg+YRX0mSJEnSoBl8NVOSnJzkliS7kuxMcmG7/dgkv0zycHt/TLv9uPb1zyS5fMm+bk3yYJK729vxkxiTpkfH/XVUkvkkDyV5IMnZkxiTpkdX/ZXk6EXz1t1J9iX5zoSGpSnS8Ry2Ocm9Se5JcnOS105iTJoeHffXR9ve2pnkskmMR/3jqc6aKUlOBE6sqh1JjgbuAs4CzgOeqqpvJvkicExVfSHJKmATsB5YX1UXLNrXrcBFVXXnmIehKdVxf30NWFFVX0lyBHBsVe0b85A0RbrsryX7vQv4XFXdNo5xaHp11WNJ5oDHgVOral8bTJ6tqm1jH5SmRof9dRzwJ+AtVfVkkiuBH1TVr8c/KvWJR3w1U6pqb1XtaH9+GtgFvB74MHBl+7IraSZiqupAVd0OPDf+atU3HffXJ4BvtK9bMPRqFPNXklOA44HfjK5y9UWHPZb2tipJgFfTBGHNsA77643AQ1X1ZPv4V4BnRemQDL6aWUnW0fwl8Y/ACVW1F5qJmeaD4P/j++2pghe3b+4SsLz+SrK6/fGSJDuSbE9ywgjLVc90NH8BbAauLU//0hLL6bGqeh74FHAv7ZFf4IpR1qt+WeYc9mfgzUnWtWcXnAWcPLpqNRQGX82kJK8Crgc+W1X/fJm72VJVpwHvam/ndlWf+q2D/poD3gD8tqpOB34PfKvDEtVjHc1fB30MuGb5VWlIlttjSY6kCb6bgJOAe4AvdVqkemu5/VVVf6fpr2tpzlbZDbzQZY0aJoOvZk77hnw9cHVV/aTd/ER77cnBa1D+dqj9VNWe9v5p4EfAW0dTsfqko/7aDzwL3NA+3g6cPoJy1TNdzV/tazcAc1V110iKVS911GMbAarqkfZsguuAd4ymYvVJh5/Bbqqqt1XV24EHgYdHVbOGw+CrmdKejnwFsKuqvr3oqZ8CW9uftwI3HmI/cwdXqGwn8Q8C93Vfsfqkq/5qPyjeBJzZbno3cH+nxap3uuqvRTbj0V4t0mGP7QFOTfK69vF7aK7n1Azrcg5L+00a7QrQnwa+1221GiJXddZMSfJOmtNi7gUW2s1fprnG5DpgDfAY8JGqeqr9N7tpFuY4CvgH8F7gUeA24EhgBc3CCp+vqhfHNBRNoa76q6ruT7IWuApYDTwJfLyqHhvXWDR9uuyv9rm/AB+oqgfGNwpNs47nsE8CFwLP07xnnldV+8c2GE2djvvrGmBDu4+vV9WPxzQM9ZjBV5IkSZI0aJ7qLEmSJEkaNIOvJEmSJGnQDL6SJEmSpEEz+EqSJEmSBs3gK0mSJEkaNIOvJEk9ksbtSd6/aNs5SW6eZF2SJE0zv85IkqSeSbIe2A5sovku8buB91XVIy9jXyv8DnJJ0tAZfCVJ6qEklwEHgFXt/VrgNGAO2FZVNyZZB1zVvgbggqr6XZIzga8Ce4GNVXXqeKuXJGm8DL6SJPVQklXADuDfwM+AnVX1wySrgTtojgYXsFBVzyU5Bbimqs5og+/PgfVV9ddJ1C9J0jjNTboASZJ0+KrqQJJrgWeAc4APJbmoffoVwBrgceDyJBuBF4E3LdrFHYZeSdKsMPhKktRfC+0twNlV9eDiJ5NsA54ANtAsaPncoqcPjKlGSZImzlWdJUnqv18An0kSgCSb2u2vAfZW1QJwLs1CWJIkzRyDryRJ/XcJcCRwT5L72scA3wW2JvkDzWnOHuWVJM0kF7eSJEmSJA2aR3wlSZIkSYNm8JUkSZIkDZrBV5IkSZI0aAZfSZIkSdKgGXwlSZIkSYNm8JUkSZIkDZrBV5IkSZI0aAZfSZIkSdKg/QdAHRTwdn3haAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,microzoojan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,microzoofeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,microzoomar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Microzooplankon Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Surface Microzooplankon Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average depth-integrated zooplankton concentration (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783ef2fe50>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,intzoojan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,intzoofeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,intzoomar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Zooplankon Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Depth-integrated Zooplankon Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average depth-integrated mesozooplankton concentration (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783ee78eb0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,intmesozoojan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,intmesozoofeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,intmesozoomar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Mesozooplankon Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Depth-integrated Mesozooplankon Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly average depth-integrated microzooplankton concentration (January-March)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783edbbdf0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,intmicrozoojan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,intmicrozoofeb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,intmicrozoomar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Microzooplankon Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Depth-integrated Microzooplankon Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "ax.invert_yaxis()\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nitrate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "mid-depth nitrate, say 30-90m (try for each location)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783ecd6f10>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,midno3jan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,midno3feb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,midno3mar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Mid-depth (30-90m) Nitrate Concentration by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nitrate concentration in deep SoG (below 250 m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f783ec29850>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "p1=ax.plot(years,deepno3jan, '-',color='green',label='January Average')\n",
    "p2=ax.plot(years,deepno3feb, '-',color='c',label='February Average')\n",
    "p3=ax.plot(years,deepno3mar, '-',color='orchid',label='March Average')\n",
    "ax.set_ylabel('Concentration ($\\mu$M N)')\n",
    "ax.set_xlabel('Year')\n",
    "ax.set_title('Deep (below 250m) Nitrate Concentration Throughout SoG by Year')\n",
    "ax.set_xticks([2015,2016,2017,2018,2019])\n",
    "ax.legend(handles=[p1[0],p2[0],p3[0]],bbox_to_anchor=(-0.25, 1.0), loc='upper left')\n",
    "\n",
    "ax1=ax.twinx()\n",
    "p4=ax1.plot(years,yearday1, 'o',color='firebrick',label='Metric1')\n",
    "p5=ax1.plot(years,yearday2, 'o',color='b',label='Metric2')\n",
    "p6=ax1.plot(years,yearday3, 'o',color='orange',label='Metric3')\n",
    "ax1.set_ylabel('Year Day')\n",
    "ax1.legend(handles=[p4[0],p5[0],p6[0]],bbox_to_anchor=(1.05, 1.0), loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (py39)",
   "language": "python",
   "name": "py39"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}